From 65a9c9aeaa64f436d22a7901f04b212291471d7e Mon Sep 17 00:00:00 2001 From: George Stuart Grattan Jr Date: Fri, 25 Oct 2024 14:36:04 -0600 Subject: [PATCH 01/35] Added extra flags to EstimateMetaData object --- src/qca/utils/utils.py | 3 +++ 1 file changed, 3 insertions(+) diff --git a/src/qca/utils/utils.py b/src/qca/utils/utils.py index d130b53..664ff6a 100644 --- a/src/qca/utils/utils.py +++ b/src/qca/utils/utils.py @@ -23,6 +23,9 @@ class EstimateMetaData: size: str task: str implementations: str + is_extrapolated: bool + bits_precision: int + trotter_layers: int value_per_circuit: float=None repetitions_per_application: int=None From 78a1e1cfef5c597d91e5921c613b834e4a754d9f Mon Sep 17 00:00:00 2001 From: George Stuart Grattan Jr Date: Fri, 25 Oct 2024 15:33:04 -0600 Subject: [PATCH 02/35] Integrated the is_extrapolated and other flags with the DickieModel.py script --- scripts/DickeModel.py | 8 +++++++- src/qca/utils/algo_utils.py | 1 + src/qca/utils/utils.py | 3 ++- 3 files changed, 10 insertions(+), 2 deletions(-) diff --git a/scripts/DickeModel.py b/scripts/DickeModel.py index 3edbfe1..6e8474a 100644 --- a/scripts/DickeModel.py +++ b/scripts/DickeModel.py @@ -30,6 +30,7 @@ def main(args): value = args.value repetitions = args.repetitions circuit_write = args.circuit_write + is_extrapolated = args.extrapolate ham_dicke = dicke_model_qubit_hamiltonian(n_s = n_s, n_b = n_b, omega_c = omega_c, omega_o = omega_o, lam = lam) @@ -61,7 +62,10 @@ def main(args): category='scientific', size=f'{n_b} + 1 + {n_s}', task='Ground State Energy Estimation', - implementations=f'GSEE, evolution_time={t_dicke}, bits_precision={bits_precision_dicke}, trotter_order={trotter_order_dicke}, n_s={n_s}, n_b={n_b}', + implementations=f'GSEE, evolution_time={t_dicke}, trotter_order={trotter_order_dicke}, n_s={n_s}, n_b={n_b}', + is_extrapolated=is_extrapolated, + bits_precision = bits_precision_dicke, + trotter_layers=trotter_steps_dicke, value_per_circuit=value_per_circuit, repetitions_per_application=repetitions ) @@ -77,6 +81,7 @@ def main(args): phase_offset=dicke_phase_offset, bits_precision=bits_precision_dicke, circuit_name=name, + is_extrapolated = is_extrapolated, metadata = dicke_metadata, write_circuits=circuit_write ) @@ -105,6 +110,7 @@ def parse_arguments(): parser.add_argument('-v', '--value', type=float, default=0, help='value of the total application') parser.add_argument('-r', '--repetitions', type=int, default=1, help='repetitions needed to achieve value of computatation (not runs of this script)') parser.add_argument('-c', '--circuit_write', default=False, action='store_true') + parser.add_argument('-x', '--extrapolate', default=False, action='store_true') return parser if __name__ == "__main__": diff --git a/src/qca/utils/algo_utils.py b/src/qca/utils/algo_utils.py index 418b2a6..07c1959 100644 --- a/src/qca/utils/algo_utils.py +++ b/src/qca/utils/algo_utils.py @@ -189,6 +189,7 @@ def gsee_resource_estimation( bits_precision:int, phase_offset:float, circuit_name:str='Hamiltonian', + is_extrapolated:bool=False, include_nested_resources:bool=True, metadata:EstimateMetaData=None, include_classical_bits:bool=False, diff --git a/src/qca/utils/utils.py b/src/qca/utils/utils.py index 664ff6a..f4a1d16 100644 --- a/src/qca/utils/utils.py +++ b/src/qca/utils/utils.py @@ -221,6 +221,7 @@ def circuit_estimate( algo_name: str, include_nested_resources:bool, bits_precision:int=1, + is_extrapolated:bool=False, write_circuits:bool = False ) -> dict: if not os.path.exists(outdir): @@ -270,7 +271,7 @@ def circuit_estimate( subcircuit_name = subcircuit_counts[gate][2] resource_estimate = gen_resource_estimate( subcircuit, - is_extrapolated=False, + is_extrapolated=is_extrapolated, circ_occurences=occurence, bits_precision=bits_precision ) From c70fc74316a36ac294fb90d8c0aa0e7dfa78b1d7 Mon Sep 17 00:00:00 2001 From: George Stuart Grattan Jr Date: Thu, 31 Oct 2024 12:01:19 -0600 Subject: [PATCH 03/35] Resolved hardcoding dependencies in estimate_trotter --- src/qca/utils/algo_utils.py | 14 ++++++++++---- 1 file changed, 10 insertions(+), 4 deletions(-) diff --git a/src/qca/utils/algo_utils.py b/src/qca/utils/algo_utils.py index 07c1959..7004ac8 100644 --- a/src/qca/utils/algo_utils.py +++ b/src/qca/utils/algo_utils.py @@ -109,9 +109,12 @@ def estimate_trotter( evolution_time: float, energy_precision: float, outdir:str, + trotter_order: int = 2, metadata: EstimateMetaData=None, hamiltonian_name:str='hamiltonian', write_circuits:bool=False, + is_extrapolated: bool = True, + algo_name: str = 'TrotterStep', nsteps:int=None, include_nested_resources:bool=True ) -> Circuit: @@ -119,6 +122,7 @@ def estimate_trotter( if not os.path.exists(outdir): os.makedirs(outdir) + #TODO: Modify MetaData object in this case if not nsteps: t0 = time.perf_counter() bounded_error = error_bound(list(openfermion_hamiltonian.get_operators()),tight=False) @@ -134,10 +138,10 @@ def estimate_trotter( t1 = time.perf_counter() elapsed = t1 - t0 print(f'Time to find term ordering: {elapsed} seconds') - t0 = time.perf_counter() + #generates the circuit for a single trotter step and extrapolates the rest trotter_circuit_of = trotterize_exp_qubop_to_qasm(openfermion_hamiltonian, - trotter_order=2, + trotter_order=trotter_order, evolution_time=evolution_time/nsteps, term_ordering=term_ordering) t1 = time.perf_counter() @@ -167,8 +171,8 @@ def estimate_trotter( logical_re = estimate_cpt_resources( cpt_circuit=cpt_trotter, outdir=outdir, - is_extrapolated=True, - algo_name='TrotterStep', + is_extrapolated=is_extrapolated, + algo_name= algo_name, trotter_steps=nsteps, include_nested_resources=include_nested_resources ) @@ -210,6 +214,7 @@ def gsee_resource_estimation( gse_circuit.generate_circuit() pe_circuit = gse_circuit.pe_circuit + #TODO: Fix Hardcoding if is_extrapolated and algo_name t0 = time.perf_counter() logical_re = circuit_estimate( circuit=pe_circuit, @@ -218,6 +223,7 @@ def gsee_resource_estimation( algo_name='GSEE', include_nested_resources=include_nested_resources, bits_precision=bits_precision, + is_extrapolated=is_extrapolated, write_circuits=write_circuits ) outfile = f'{outdir}{circuit_name}_re.json' From 09ec42e98bb8c2bae9cafc312890334cdc44b934 Mon Sep 17 00:00:00 2001 From: George Stuart Grattan Jr Date: Thu, 31 Oct 2024 12:05:44 -0600 Subject: [PATCH 04/35] Resolved hardcoding dependencies in gsee_resource_estimation() --- src/qca/utils/algo_utils.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/qca/utils/algo_utils.py b/src/qca/utils/algo_utils.py index 7004ac8..16925da 100644 --- a/src/qca/utils/algo_utils.py +++ b/src/qca/utils/algo_utils.py @@ -194,6 +194,7 @@ def gsee_resource_estimation( phase_offset:float, circuit_name:str='Hamiltonian', is_extrapolated:bool=False, + algo_name='GSEE', include_nested_resources:bool=True, metadata:EstimateMetaData=None, include_classical_bits:bool=False, @@ -214,13 +215,12 @@ def gsee_resource_estimation( gse_circuit.generate_circuit() pe_circuit = gse_circuit.pe_circuit - #TODO: Fix Hardcoding if is_extrapolated and algo_name t0 = time.perf_counter() logical_re = circuit_estimate( circuit=pe_circuit, outdir=outdir, numsteps=numsteps, - algo_name='GSEE', + algo_name=algo_name, include_nested_resources=include_nested_resources, bits_precision=bits_precision, is_extrapolated=is_extrapolated, From b34e7aee1b311b399e3ab7b04ac533fac0e7ceeb Mon Sep 17 00:00:00 2001 From: George Stuart Grattan Jr Date: Thu, 31 Oct 2024 12:11:15 -0600 Subject: [PATCH 05/35] Resolved hardcoding dependenct in estimate_qsp(), also refactored argument ordering in the estimate methods to be more consistent --- src/qca/utils/algo_utils.py | 14 ++++++++------ 1 file changed, 8 insertions(+), 6 deletions(-) diff --git a/src/qca/utils/algo_utils.py b/src/qca/utils/algo_utils.py index 16925da..e592c98 100644 --- a/src/qca/utils/algo_utils.py +++ b/src/qca/utils/algo_utils.py @@ -34,8 +34,9 @@ def estimate_qsp( numsteps:int, energy_precision:float, outdir:str, - hamiltonian_name:str='hamiltonian', metadata: EstimateMetaData = None, + algo_name: str = 'QSP', + hamiltonian_name:str='hamiltonian', write_circuits:bool=False, include_nested_resources:bool=True ) -> Circuit: @@ -58,7 +59,7 @@ def estimate_qsp( circuit=qsp_circuit, outdir=outdir, numsteps=numsteps, - algo_name='QSP', + algo_name=algo_name, write_circuits=write_circuits, include_nested_resources=include_nested_resources ) @@ -111,10 +112,10 @@ def estimate_trotter( outdir:str, trotter_order: int = 2, metadata: EstimateMetaData=None, + algo_name: str = 'TrotterStep', hamiltonian_name:str='hamiltonian', - write_circuits:bool=False, is_extrapolated: bool = True, - algo_name: str = 'TrotterStep', + write_circuits:bool=False, nsteps:int=None, include_nested_resources:bool=True ) -> Circuit: @@ -192,11 +193,12 @@ def gsee_resource_estimation( precision_order:int, bits_precision:int, phase_offset:float, + metadata:EstimateMetaData=None, + algo_name='GSEE', circuit_name:str='Hamiltonian', is_extrapolated:bool=False, - algo_name='GSEE', include_nested_resources:bool=True, - metadata:EstimateMetaData=None, + include_classical_bits:bool=False, write_circuits:bool=False ) -> Circuit: From 3ccc8a4d45fcadd372ca24ace3581226262df6b2 Mon Sep 17 00:00:00 2001 From: George Stuart Grattan Jr Date: Thu, 31 Oct 2024 12:59:59 -0600 Subject: [PATCH 06/35] Implemented Implementation specific MetaData classes that inherit from EstimateMetaData --- src/qca/utils/utils.py | 29 +++++++++++++++++++++++++---- 1 file changed, 25 insertions(+), 4 deletions(-) diff --git a/src/qca/utils/utils.py b/src/qca/utils/utils.py index f4a1d16..6d88c5b 100644 --- a/src/qca/utils/utils.py +++ b/src/qca/utils/utils.py @@ -22,13 +22,34 @@ class EstimateMetaData: category: str size: str task: str - implementations: str - is_extrapolated: bool - bits_precision: int - trotter_layers: int value_per_circuit: float=None repetitions_per_application: int=None +@dataclass +class GSEEMetaData(EstimateMetaData): + + evolution_time: float + bits_precision: int + trotter_order: int + is_extrapolated: bool + implementation: str = "GSEE" +@dataclass +class TrotterizationMetaData(EstimateMetaData): + evolution_time: float #NOTE: This is JT in the current implementation + trotter_layers: int + trotter_order: int + energy_precision: float + is_extrapolated:bool + implementation: str= "Trotterization" + +@dataclass +class QSPMetaData(EstimateMetaData): + evolution_time: float #NOTE: This is JT in the current implementation + trotter_layers: int + trotter_order: int + energy_precision: float + implementation:str = "QSP" + def count_gates(cpt_circuit: cirq.AbstractCircuit) -> int: count = 0 for moment in cpt_circuit: From c4793176dabd42f1d83ce749d16b67234670dff1 Mon Sep 17 00:00:00 2001 From: George Stuart Grattan Jr Date: Thu, 31 Oct 2024 13:35:51 -0600 Subject: [PATCH 07/35] Fixed bug where I couldn't set default values in the EstimateMetaData data class --- src/qca/utils/utils.py | 8 +++++--- 1 file changed, 5 insertions(+), 3 deletions(-) diff --git a/src/qca/utils/utils.py b/src/qca/utils/utils.py index 6d88c5b..81b6ccd 100644 --- a/src/qca/utils/utils.py +++ b/src/qca/utils/utils.py @@ -3,7 +3,7 @@ import json import time from statistics import median -from dataclasses import dataclass +from dataclasses import dataclass, field import pandas as pd @@ -15,6 +15,7 @@ from pyLIQTR.utils.utils import count_T_gates from pyLIQTR.gate_decomp.cirq_transforms import clifford_plus_t_direct_transform +#TODO: Figure out issue with partent class with default values and child classes don't have them @dataclass class EstimateMetaData: id: str @@ -22,8 +23,8 @@ class EstimateMetaData: category: str size: str task: str - value_per_circuit: float=None - repetitions_per_application: int=None + value_per_circuit: float=field(default=None, kw_only=True) + repetitions_per_application: int=field(default=None, kw_only=True) @dataclass class GSEEMetaData(EstimateMetaData): @@ -31,6 +32,7 @@ class GSEEMetaData(EstimateMetaData): evolution_time: float bits_precision: int trotter_order: int + trotter_layers: int is_extrapolated: bool implementation: str = "GSEE" @dataclass From a92f6ff6a1ea11c0bd84b4509b3dc2bb85ccd617 Mon Sep 17 00:00:00 2001 From: George Stuart Grattan Jr Date: Thu, 31 Oct 2024 13:37:56 -0600 Subject: [PATCH 08/35] Integrated the new implementation-specific data classed with their respective estimator tool --- src/qca/utils/algo_utils.py | 11 +++++++---- 1 file changed, 7 insertions(+), 4 deletions(-) diff --git a/src/qca/utils/algo_utils.py b/src/qca/utils/algo_utils.py index e592c98..aef0c3d 100644 --- a/src/qca/utils/algo_utils.py +++ b/src/qca/utils/algo_utils.py @@ -25,7 +25,10 @@ write_qasm, circuit_estimate, estimate_cpt_resources, - EstimateMetaData + EstimateMetaData, + GSEEMetaData, + TrotterizationMetaData, + QSPMetaData ) def estimate_qsp( @@ -34,7 +37,7 @@ def estimate_qsp( numsteps:int, energy_precision:float, outdir:str, - metadata: EstimateMetaData = None, + metadata: QSPMetaData = None, algo_name: str = 'QSP', hamiltonian_name:str='hamiltonian', write_circuits:bool=False, @@ -111,7 +114,7 @@ def estimate_trotter( energy_precision: float, outdir:str, trotter_order: int = 2, - metadata: EstimateMetaData=None, + metadata: TrotterizationMetaData=None, algo_name: str = 'TrotterStep', hamiltonian_name:str='hamiltonian', is_extrapolated: bool = True, @@ -193,7 +196,7 @@ def gsee_resource_estimation( precision_order:int, bits_precision:int, phase_offset:float, - metadata:EstimateMetaData=None, + metadata:GSEEMetaData=None, algo_name='GSEE', circuit_name:str='Hamiltonian', is_extrapolated:bool=False, From a542f9be3c2dc29c4ca2707025e7026298e0519f Mon Sep 17 00:00:00 2001 From: George Stuart Grattan Jr Date: Thu, 31 Oct 2024 13:38:44 -0600 Subject: [PATCH 09/35] Integrated the new GSEEMetaData object with the DickeModel script --- scripts/DickeModel.py | 15 ++++++++++----- 1 file changed, 10 insertions(+), 5 deletions(-) diff --git a/scripts/DickeModel.py b/scripts/DickeModel.py index 6e8474a..e53ac95 100644 --- a/scripts/DickeModel.py +++ b/scripts/DickeModel.py @@ -8,7 +8,7 @@ from pyLIQTR.PhaseEstimation.pe import PhaseEstimation from networkx import path_graph, set_node_attributes, get_node_attributes, draw, draw_networkx_edge_labels from qca.utils.algo_utils import gsee_resource_estimation -from qca.utils.utils import circuit_estimate, EstimateMetaData +from qca.utils.utils import circuit_estimate, GSEEMetaData from qca.utils.hamiltonian_utils import (generate_two_orbital_nx, nx_to_two_orbital_hamiltonian, dicke_model_qubit_hamiltonian) @@ -56,18 +56,23 @@ def main(args): print('starting') value_per_circuit = value/repetitions value_per_circuit=6 - dicke_metadata = EstimateMetaData( + #TODO: See if I need to refactor the size string to include the variable names + dicke_metadata = GSEEMetaData( id=time.time_ns(), name=name, category='scientific', size=f'{n_b} + 1 + {n_s}', task='Ground State Energy Estimation', - implementations=f'GSEE, evolution_time={t_dicke}, trotter_order={trotter_order_dicke}, n_s={n_s}, n_b={n_b}', + value_per_circuit=value_per_circuit, + repetitions_per_application=repetitions, + + + evolution_time=t_dicke, + trotter_order = trotter_order_dicke, is_extrapolated=is_extrapolated, bits_precision = bits_precision_dicke, trotter_layers=trotter_steps_dicke, - value_per_circuit=value_per_circuit, - repetitions_per_application=repetitions + implementation='GSEE' ) print('Estimating Dicke') From e789e1a84d62b77037c234f4aa3fb7c679fcc979 Mon Sep 17 00:00:00 2001 From: George Stuart Grattan Jr Date: Thu, 31 Oct 2024 15:39:57 -0600 Subject: [PATCH 10/35] Integrated the new GSEEMetaData objects into the FermiHubbard scripts --- scripts/HTSC-one-band-RE.py | 21 +++++++++++++++------ scripts/HTSC-three-band-RE.py | 20 ++++++++++++++------ scripts/HTSC-two-band-RE.py | 20 ++++++++++++++------ 3 files changed, 43 insertions(+), 18 deletions(-) diff --git a/scripts/HTSC-one-band-RE.py b/scripts/HTSC-one-band-RE.py index ed83685..f2403b3 100644 --- a/scripts/HTSC-one-band-RE.py +++ b/scripts/HTSC-one-band-RE.py @@ -9,7 +9,7 @@ from pyLIQTR.PhaseEstimation.pe import PhaseEstimation from networkx import get_node_attributes, draw, draw_networkx_edge_labels from qca.utils.algo_utils import gsee_resource_estimation -from qca.utils.utils import circuit_estimate, EstimateMetaData +from qca.utils.utils import circuit_estimate, GSEEMetaData from qca.utils.hamiltonian_utils import generate_two_orbital_nx, nx_to_two_orbital_hamiltonian def main(args): @@ -25,9 +25,11 @@ def main(args): value = args.value repetitions = args.repetitions circuit_write = args.circuit_write + is_extrapolated= args.extrapolate ham = of.fermi_hubbard(lattice_size, lattice_size, tunneling=tunneling, coulomb=coulomb, periodic=False) #returns an aperiodic fermionic hamiltonian + #TODO: Fix this Hardcoding trotter_order = 2 trotter_steps = 1 #Using one trotter step for a strict lower bound with this method @@ -37,13 +39,13 @@ def main(args): E_min = -len(ham.terms) * max(abs(tunneling), abs(coulomb)) E_max = 0 omega = E_max-E_min - t = 2*np.pi/omega - phase_offset = E_max*t + evolution_time = 2*np.pi/omega + phase_offset = E_max*evolution_time gsee_args = { 'trotterize' : True, 'mol_ham' : ham, - 'ev_time' : t, + 'ev_time' : evolution_time, 'trot_ord' : trotter_order, 'trot_num' : 1 #handling adjustment in resource estimate to save time - scales circuit depth linearly. } @@ -52,7 +54,7 @@ def main(args): init_state = [0] * lattice_size * lattice_size * 2 #TODO: use Fock state from Hartree-Fock as initial state print('starting') - metadata = EstimateMetaData( + metadata = GSEEMetaData( id=time.time_ns(), name=name, category='scientific', @@ -60,7 +62,13 @@ def main(args): task='Ground State Energy Estimation', value_per_circuit=value, repetitions_per_application=repetitions, - implementations=f'GSEE, evolution_time={t}, bits_precision={bits_precision}, trotter_order={trotter_order}', + + evolution_time=evolution_time, + trotter_order=trotter_order, + is_extrapolated=is_extrapolated, + bits_precision=bits_precision, + trotter_layers=trotter_steps, + implementation="GSEE" ) print('Estimating one_band') @@ -96,6 +104,7 @@ def parse_arguments(): parser.add_argument('-v', '--value', type=float, default=0, help='value of the total application') parser.add_argument('-r', '--repetitions', type=int, default=1, help='repetitions needed to achieve value of computatation (not runs of this script)') parser.add_argument('-c', '--circuit_write', default=False, action='store_true') + parser.add_argument('-x', '--extrapolate', default=False, action='store_true') return parser if __name__ == "__main__": diff --git a/scripts/HTSC-three-band-RE.py b/scripts/HTSC-three-band-RE.py index 8b47c11..a107520 100644 --- a/scripts/HTSC-three-band-RE.py +++ b/scripts/HTSC-three-band-RE.py @@ -9,7 +9,7 @@ from pyLIQTR.PhaseEstimation.pe import PhaseEstimation from networkx import get_node_attributes, draw, draw_networkx_edge_labels from qca.utils.algo_utils import gsee_resource_estimation -from qca.utils.utils import circuit_estimate, EstimateMetaData +from qca.utils.utils import circuit_estimate, GSEEMetaData from qca.utils.hamiltonian_utils import generate_three_orbital_nx, nx_to_three_orbital_hamiltonian ## Three band @@ -35,6 +35,7 @@ def main(args): repetitions = args.repetitions directory = args.directory name = args.name + is_extrapolated = args.extrapolate bits_precision = estimate_bits_precision(args.error_precision) g = generate_three_orbital_nx(lattice_size,lattice_size) @@ -45,15 +46,15 @@ def main(args): E_min = -len(ham.terms) * max(abs(t1), abs(t2), abs(t3), abs(t4), abs(mu)) E_max = 0 omega = E_max-E_min - t = 2*np.pi/omega - phase_offset = E_max*t + evolution_time = 2*np.pi/omega + phase_offset = E_max*evolution_time init_state = [0] * n_qubits gsee_args = { 'trotterize' : True, 'mol_ham' : ham, - 'ev_time' : t, + 'ev_time' : evolution_time, 'trot_ord' : trotter_order, 'trot_num' : 1 #Accounted for in a scaling argument later } @@ -61,7 +62,7 @@ def main(args): print('starting') - metadata = EstimateMetaData( + metadata = GSEEMetaData( id=time.time_ns(), name=name, category='scientific', @@ -69,7 +70,13 @@ def main(args): task='Ground State Energy Estimation', value_per_circuit=value, repetitions_per_application=repetitions, - implementations=f'GSEE, evolution_time={t}, bits_precision={bits_precision}, trotter_order={trotter_order}', + + evolution_time=evolution_time, + trotter_order=trotter_order, + is_extrapolated=is_extrapolated, + bits_precision=bits_precision, + trotter_layers=trotter_steps, + implementation="GSEE" ) print('Estimating Circuit Resources') @@ -114,6 +121,7 @@ def parse_arguments(): parser.add_argument('-v', '--value', type=float, default=0, help='value of the total application') parser.add_argument('-r', '--repetitions', type=int, default=1, help='repetitions needed to achieve value of computatation (not runs of this script)') parser.add_argument('-c', '--circuit_write', default=False, action='store_true') + parser.add_argument('-x', '--extrapolate', default=False, action='store_true') return parser if __name__ == "__main__": diff --git a/scripts/HTSC-two-band-RE.py b/scripts/HTSC-two-band-RE.py index b688579..3c2cd8e 100644 --- a/scripts/HTSC-two-band-RE.py +++ b/scripts/HTSC-two-band-RE.py @@ -9,7 +9,7 @@ from pyLIQTR.PhaseEstimation.pe import PhaseEstimation from networkx import get_node_attributes, draw, draw_networkx_edge_labels from qca.utils.algo_utils import gsee_resource_estimation -from qca.utils.utils import circuit_estimate, EstimateMetaData +from qca.utils.utils import circuit_estimate, GSEEMetaData from qca.utils.hamiltonian_utils import generate_two_orbital_nx, nx_to_two_orbital_hamiltonian ## Two band @@ -30,6 +30,7 @@ def main(args): repetitions = args.repetitions directory = args.directory name = args.name + is_extrapolated=args.extrapolate bits_precision = estimate_bits_precision(args.error_precision) g = generate_two_orbital_nx(lattice_size,lattice_size) @@ -40,15 +41,15 @@ def main(args): E_min = -len(ham.terms) * max(abs(t1), abs(t2), abs(t3), abs(t4), abs(mu)) E_max = 0 omega = E_max-E_min - t = 2*np.pi/omega - phase_offset = E_max*t + evolution_time = 2*np.pi/omega + phase_offset = E_max*evolution_time init_state = [0] * n_qubits gsee_args = { 'trotterize' : True, 'mol_ham' : ham, - 'ev_time' : t, + 'ev_time' : evolution_time, 'trot_ord' : trotter_order, 'trot_num' : 1 #Accounted for in a scaling argument later } @@ -56,7 +57,7 @@ def main(args): print('starting') - metadata = EstimateMetaData( + metadata = GSEEMetaData( id=time.time_ns(), name=name, category='scientific', @@ -64,7 +65,13 @@ def main(args): task='Ground State Energy Estimation', value_per_circuit=value, repetitions_per_application=repetitions, - implementations=f'GSEE, evolution_time={t}, bits_precision={bits_precision}, trotter_order={trotter_order}', + + evolution_time=evolution_time, + trotter_order=trotter_order, + is_extrapolated=is_extrapolated, + bits_precision=bits_precision, + trotter_layers=trotter_steps, + implementation="GSEE" ) print('Estimating Circuit Resources') @@ -104,6 +111,7 @@ def parse_arguments(): parser.add_argument('-v', '--value', type=float, default=0, help='value of the total application') parser.add_argument('-r', '--repetitions', type=int, default=1, help='repetitions needed to achieve value of computatation (not runs of this script)') parser.add_argument('-c', '--circuit_write', default=False, action='store_true') + parser.add_argument('-x', '--extrapolate', default=False, action='store_true') return parser if __name__ == "__main__": From 28ebadccdc94c58b2fdfd4134afd161ea98f2aa3 Mon Sep 17 00:00:00 2001 From: George Stuart Grattan Jr Date: Thu, 31 Oct 2024 15:53:00 -0600 Subject: [PATCH 11/35] Fixed a bug where I didn't pass is_extrapolated into gsee_resource_estimation() --- scripts/HTSC-one-band-RE.py | 1 + scripts/HTSC-three-band-RE.py | 1 + scripts/HTSC-two-band-RE.py | 1 + 3 files changed, 3 insertions(+) diff --git a/scripts/HTSC-one-band-RE.py b/scripts/HTSC-one-band-RE.py index f2403b3..16de215 100644 --- a/scripts/HTSC-one-band-RE.py +++ b/scripts/HTSC-one-band-RE.py @@ -83,6 +83,7 @@ def main(args): bits_precision=bits_precision, circuit_name=name, metadata=metadata, + is_extrapolated=is_extrapolated, write_circuits=args.circuit_write) t1 = time.perf_counter() print(f'Time to estimate one_band: {t1-t0}') diff --git a/scripts/HTSC-three-band-RE.py b/scripts/HTSC-three-band-RE.py index a107520..8235ffa 100644 --- a/scripts/HTSC-three-band-RE.py +++ b/scripts/HTSC-three-band-RE.py @@ -90,6 +90,7 @@ def main(args): phase_offset=phase_offset, bits_precision=bits_precision, circuit_name=name, + is_extrapolated = is_extrapolated, metadata=metadata, write_circuits=args.circuit_write) t1 = time.perf_counter() diff --git a/scripts/HTSC-two-band-RE.py b/scripts/HTSC-two-band-RE.py index 3c2cd8e..3616876 100644 --- a/scripts/HTSC-two-band-RE.py +++ b/scripts/HTSC-two-band-RE.py @@ -85,6 +85,7 @@ def main(args): phase_offset=phase_offset, bits_precision=bits_precision, circuit_name=name, + is_extrapolated=is_extrapolated, metadata=metadata, write_circuits=args.circuit_write) t1 = time.perf_counter() From 40344143fb029b785768d1a4f716c69c93f5560f Mon Sep 17 00:00:00 2001 From: George Stuart Grattan Jr Date: Thu, 31 Oct 2024 15:56:02 -0600 Subject: [PATCH 12/35] Integrated the new GSEEMetaData objects into the TavisCummings script --- scripts/TavisCummingsModel.py | 18 ++++++++++++++---- 1 file changed, 14 insertions(+), 4 deletions(-) diff --git a/scripts/TavisCummingsModel.py b/scripts/TavisCummingsModel.py index 2480f65..3278b86 100644 --- a/scripts/TavisCummingsModel.py +++ b/scripts/TavisCummingsModel.py @@ -8,7 +8,7 @@ from pyLIQTR.PhaseEstimation.pe import PhaseEstimation from networkx import path_graph, set_node_attributes, get_node_attributes, draw, draw_networkx_edge_labels from qca.utils.algo_utils import gsee_resource_estimation -from qca.utils.utils import circuit_estimate, EstimateMetaData +from qca.utils.utils import circuit_estimate, GSEEMetaData from qca.utils.hamiltonian_utils import (generate_two_orbital_nx, nx_to_two_orbital_hamiltonian, tavis_cummings_model_qubit_hamiltonian) @@ -29,6 +29,7 @@ def main(args): value = args.value repetitions = args.repetitions circuit_write = args.circuit_write + is_extrapolated = args.extrapolate ham_tavis_cummings = tavis_cummings_model_qubit_hamiltonian(n_s = n_s, n_b = n_b, omega_c = omega_c, omega_o = omega_o, lam = lam) @@ -53,15 +54,22 @@ def main(args): print('starting') value_per_circuit = value/repetitions - tavis_cummings_metadata = EstimateMetaData( + tavis_cummings_metadata = GSEEMetaData( id=time.time_ns(), name=name, category='scientific', size=f'{n_b} + 1 + {n_s}', task='Ground State Energy Estimation', - implementations=f'GSEE, evolution_time={t_tavis_cummings}, bits_precision={bits_precision_tavis_cummings}, trotter_order={trotter_order_tavis_cummings}, n_s={n_s}, n_b={n_b}', value_per_circuit=value_per_circuit, - repetitions_per_application=repetitions + repetitions_per_application=repetitions, + + + evolution_time=t_tavis_cummings, + trotter_order = trotter_order_tavis_cummings, + is_extrapolated=is_extrapolated, + bits_precision = bits_precision_tavis_cummings, + trotter_layers=trotter_steps_tavis_cummings, + implementation='GSEE' ) print('Estimating tavis_cummings') @@ -76,6 +84,7 @@ def main(args): bits_precision=bits_precision_tavis_cummings, circuit_name=name, metadata = tavis_cummings_metadata, + is_extrapolated=is_extrapolated, write_circuits=circuit_write ) t1 = time.perf_counter() @@ -103,6 +112,7 @@ def parse_arguments(): parser.add_argument('-v', '--value', type=float, default=0, help='value of the total application') parser.add_argument('-r', '--repetitions', type=int, default=1, help='repetitions needed to achieve value of computatation (not runs of this script)') parser.add_argument('-c', '--circuit_write', default=False, action='store_true') + parser.add_argument('-x', '--extrapolate', default=False, action='store_true') return parser if __name__ == "__main__": From 87843e781147d2e5804f23bbbe9ba677043c15ba Mon Sep 17 00:00:00 2001 From: George Stuart Grattan Jr Date: Thu, 31 Oct 2024 16:18:10 -0600 Subject: [PATCH 13/35] Removed unnecessary trotter_order parameter from QSPMetaData object --- src/qca/utils/utils.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/qca/utils/utils.py b/src/qca/utils/utils.py index 81b6ccd..c68610e 100644 --- a/src/qca/utils/utils.py +++ b/src/qca/utils/utils.py @@ -35,6 +35,7 @@ class GSEEMetaData(EstimateMetaData): trotter_layers: int is_extrapolated: bool implementation: str = "GSEE" +#TODO: Potentially add gate_synth_accuracy to the following two dataclasses @dataclass class TrotterizationMetaData(EstimateMetaData): evolution_time: float #NOTE: This is JT in the current implementation @@ -48,7 +49,6 @@ class TrotterizationMetaData(EstimateMetaData): class QSPMetaData(EstimateMetaData): evolution_time: float #NOTE: This is JT in the current implementation trotter_layers: int - trotter_order: int energy_precision: float implementation:str = "QSP" From 482e069824428943af5ea74723fcee0c070d2c64 Mon Sep 17 00:00:00 2001 From: George Stuart Grattan Jr Date: Fri, 1 Nov 2024 14:08:20 -0600 Subject: [PATCH 14/35] Integrated the TrotterizationMetaData and QSPMetaData objects into RuCl-RE.py --- scripts/RuCl-RE.py | 46 +++++++++++++++++++++++++++++++++++++--------- 1 file changed, 37 insertions(+), 9 deletions(-) diff --git a/scripts/RuCl-RE.py b/scripts/RuCl-RE.py index f8c125d..d3cc05d 100644 --- a/scripts/RuCl-RE.py +++ b/scripts/RuCl-RE.py @@ -6,7 +6,7 @@ from networkx import Graph from pandas import DataFrame from networkx.generators.lattice import hexagonal_lattice_graph -from qca.utils.utils import EstimateMetaData +from qca.utils.utils import TrotterizationMetaData, QSPMetaData from qca.utils.algo_utils import estimate_trotter, estimate_qsp from qca.utils.hamiltonian_utils import ( flatten_nx_graph, @@ -192,32 +192,60 @@ def generate_rucl_re( ) H_rucl_pyliqtr = pyH(H_rucl) openfermion_hamiltonian_rucl = pyliqtr_hamiltonian_to_openfermion_qubit_operator(H_rucl_pyliqtr) + + #TODO: Handle the Hardcoding here - I just pulled the hardcoded values up from internal functions and centralized them here nsteps = 1500000 - metadata = EstimateMetaData( + gate_synth_accuracy = 1e-10 + trotter_order = 2 + is_extrapolated=True + + + trotter_metadata = TrotterizationMetaData( id=f'{time.time_ns()}', name=f'RuCl_row_{rucl_idx}', category='scientific', size=f'lattice_size: {lattice_size}', task='Time-Dependent Dynamics', - implementations='trotterization, JT=1000, gate_synth_accuracy=1e-10, numsteps=1500000, energy_precision=1e-3', + + evolution_time = evolution_time, + nsteps = nsteps, + trotter_order = trotter_order, + energy_precision=energy_precision, + is_extrapolated=is_extrapolated, + implementation = 'Trotterization' ) estimate_trotter( openfermion_hamiltonian=openfermion_hamiltonian_rucl, evolution_time=evolution_time, energy_precision=energy_precision, - metadata=metadata, + metadata=trotter_metadata, outdir=outdir, + trotter_order=trotter_order, + hamiltonian_name=f'trotter_rucl_size_{lattice_size}_row_{rucl_idx}', - nsteps=nsteps + nsteps=nsteps, + is_extrapolated=is_extrapolated ) - metadata.implementations='QSP, JT=1000, gate_synth_accuracy=1e-10, numsteps=1500000, energy_precision=1e-3' - metadata.id = f'{time.time_ns()}' + + qsp_metadata = QSPMetaData( + id =f'{time.time_ns()}', + name=f'RuCl_row_{rucl_idx}', + category='scientific', + size=f'lattice_size: {lattice_size}', + task='Time-Dependent Dynamics', + + evolution_time = evolution_time, + nsteps = nsteps, + energy_precision=energy_precision, + implementation = 'Trotterization' + ) + estimate_qsp( pyliqtr_hamiltonian=H_rucl_pyliqtr, evolution_time=evolution_time, - numsteps=nsteps, + nsteps=nsteps, energy_precision=energy_precision, - metadata=metadata, + metadata=qsp_metadata, outdir=outdir, hamiltonian_name=f'qsp_rucl_size_{lattice_size}_row_{rucl_idx}', write_circuits=False From 3f2f51ea7d19a82cb069cba433f9f9cf1445e2f1 Mon Sep 17 00:00:00 2001 From: George Stuart Grattan Jr Date: Fri, 1 Nov 2024 14:10:34 -0600 Subject: [PATCH 15/35] Made the naming for the number of trotter steps more consistent between functions and classes -> nsteps --- scripts/AP-RE.py | 2 ++ scripts/DickeModel.py | 4 ++-- scripts/HTSC-one-band-RE.py | 4 ++-- scripts/HTSC-three-band-RE.py | 4 ++-- scripts/HTSC-two-band-RE.py | 4 ++-- scripts/TavisCummingsModel.py | 4 ++-- src/qca/utils/algo_utils.py | 10 +++++----- 7 files changed, 17 insertions(+), 15 deletions(-) diff --git a/scripts/AP-RE.py b/scripts/AP-RE.py index 8d1b87c..84aceec 100644 --- a/scripts/AP-RE.py +++ b/scripts/AP-RE.py @@ -4,6 +4,8 @@ from concurrent.futures import ThreadPoolExecutor, as_completed, ProcessPoolExecutor from qca.utils.chemistry_utils import load_pathway, generate_electronic_hamiltonians, gsee_molecular_hamiltonian +#TODO: Integrate the MetaData classes into this functionality + @dataclass class pathway_info: pathway: list[int] diff --git a/scripts/DickeModel.py b/scripts/DickeModel.py index e53ac95..035e544 100644 --- a/scripts/DickeModel.py +++ b/scripts/DickeModel.py @@ -71,7 +71,7 @@ def main(args): trotter_order = trotter_order_dicke, is_extrapolated=is_extrapolated, bits_precision = bits_precision_dicke, - trotter_layers=trotter_steps_dicke, + nsteps=trotter_steps_dicke, implementation='GSEE' ) @@ -79,7 +79,7 @@ def main(args): t0 = time.perf_counter() estimate = gsee_resource_estimation( outdir=directory, - numsteps=trotter_steps_dicke, + nsteps=trotter_steps_dicke, gsee_args=args_dicke, init_state=init_state_dicke, precision_order=1, #actual precision bits accounted as scaling factors in the resource estimate diff --git a/scripts/HTSC-one-band-RE.py b/scripts/HTSC-one-band-RE.py index 16de215..b87a8cc 100644 --- a/scripts/HTSC-one-band-RE.py +++ b/scripts/HTSC-one-band-RE.py @@ -67,7 +67,7 @@ def main(args): trotter_order=trotter_order, is_extrapolated=is_extrapolated, bits_precision=bits_precision, - trotter_layers=trotter_steps, + nsteps=trotter_steps, implementation="GSEE" ) @@ -75,7 +75,7 @@ def main(args): t0 = time.perf_counter() estimate = gsee_resource_estimation( outdir=directory, - numsteps=trotter_steps, + nsteps=trotter_steps, gsee_args=gsee_args, init_state=init_state, precision_order=1, diff --git a/scripts/HTSC-three-band-RE.py b/scripts/HTSC-three-band-RE.py index 8235ffa..e51656b 100644 --- a/scripts/HTSC-three-band-RE.py +++ b/scripts/HTSC-three-band-RE.py @@ -75,7 +75,7 @@ def main(args): trotter_order=trotter_order, is_extrapolated=is_extrapolated, bits_precision=bits_precision, - trotter_layers=trotter_steps, + nsteps=trotter_steps, implementation="GSEE" ) @@ -83,7 +83,7 @@ def main(args): t0 = time.perf_counter() estimate = gsee_resource_estimation( outdir=directory, - numsteps=trotter_steps, + nsteps=trotter_steps, gsee_args=gsee_args, init_state=init_state, precision_order=1, diff --git a/scripts/HTSC-two-band-RE.py b/scripts/HTSC-two-band-RE.py index 3616876..2c0d42d 100644 --- a/scripts/HTSC-two-band-RE.py +++ b/scripts/HTSC-two-band-RE.py @@ -70,7 +70,7 @@ def main(args): trotter_order=trotter_order, is_extrapolated=is_extrapolated, bits_precision=bits_precision, - trotter_layers=trotter_steps, + nsteps=trotter_steps, implementation="GSEE" ) @@ -78,7 +78,7 @@ def main(args): t0 = time.perf_counter() estimate = gsee_resource_estimation( outdir=directory, - numsteps=trotter_steps, + nsteps=trotter_steps, gsee_args=gsee_args, init_state=init_state, precision_order=1, diff --git a/scripts/TavisCummingsModel.py b/scripts/TavisCummingsModel.py index 3278b86..98b5496 100644 --- a/scripts/TavisCummingsModel.py +++ b/scripts/TavisCummingsModel.py @@ -68,7 +68,7 @@ def main(args): trotter_order = trotter_order_tavis_cummings, is_extrapolated=is_extrapolated, bits_precision = bits_precision_tavis_cummings, - trotter_layers=trotter_steps_tavis_cummings, + nsteps=trotter_steps_tavis_cummings, implementation='GSEE' ) @@ -76,7 +76,7 @@ def main(args): t0 = time.perf_counter() estimate = gsee_resource_estimation( outdir=directory, - numsteps=trotter_steps_tavis_cummings, + nsteps=trotter_steps_tavis_cummings, gsee_args=args_tavis_cummings, init_state=init_state_tavis_cummings, precision_order=1, #actual precision bits accounted as scaling factors in the resource estimate diff --git a/src/qca/utils/algo_utils.py b/src/qca/utils/algo_utils.py index aef0c3d..cdd01e2 100644 --- a/src/qca/utils/algo_utils.py +++ b/src/qca/utils/algo_utils.py @@ -34,7 +34,7 @@ def estimate_qsp( pyliqtr_hamiltonian: Hamiltonian, evolution_time:float, - numsteps:int, + nsteps:int, energy_precision:float, outdir:str, metadata: QSPMetaData = None, @@ -43,7 +43,7 @@ def estimate_qsp( write_circuits:bool=False, include_nested_resources:bool=True ) -> Circuit: - timestep_of_interest=evolution_time/numsteps + timestep_of_interest=evolution_time/nsteps random.seed(0) np.random.seed(0) t0 = time.perf_counter() @@ -61,7 +61,7 @@ def estimate_qsp( logical_re = circuit_estimate( circuit=qsp_circuit, outdir=outdir, - numsteps=numsteps, + numsteps=nsteps, algo_name=algo_name, write_circuits=write_circuits, include_nested_resources=include_nested_resources @@ -190,7 +190,7 @@ def estimate_trotter( def gsee_resource_estimation( outdir:str, - numsteps:int, + nsteps:int, gsee_args:dict, init_state:list, precision_order:int, @@ -224,7 +224,7 @@ def gsee_resource_estimation( logical_re = circuit_estimate( circuit=pe_circuit, outdir=outdir, - numsteps=numsteps, + numsteps=nsteps, algo_name=algo_name, include_nested_resources=include_nested_resources, bits_precision=bits_precision, From 9137290f28f793f19ccdc2ea876c630714ae03d7 Mon Sep 17 00:00:00 2001 From: George Stuart Grattan Jr Date: Fri, 1 Nov 2024 16:19:12 -0600 Subject: [PATCH 16/35] Set default value for nsteps in TrotterizationMetaData --- src/qca/utils/utils.py | 7 +++---- 1 file changed, 3 insertions(+), 4 deletions(-) diff --git a/src/qca/utils/utils.py b/src/qca/utils/utils.py index c68610e..4195a45 100644 --- a/src/qca/utils/utils.py +++ b/src/qca/utils/utils.py @@ -28,27 +28,26 @@ class EstimateMetaData: @dataclass class GSEEMetaData(EstimateMetaData): - evolution_time: float bits_precision: int trotter_order: int - trotter_layers: int + nsteps: int is_extrapolated: bool implementation: str = "GSEE" #TODO: Potentially add gate_synth_accuracy to the following two dataclasses @dataclass class TrotterizationMetaData(EstimateMetaData): evolution_time: float #NOTE: This is JT in the current implementation - trotter_layers: int trotter_order: int energy_precision: float is_extrapolated:bool + nsteps: int=None implementation: str= "Trotterization" @dataclass class QSPMetaData(EstimateMetaData): evolution_time: float #NOTE: This is JT in the current implementation - trotter_layers: int + nsteps: int energy_precision: float implementation:str = "QSP" From ea869846b08fc6fa2740531f2c053bcb6e9bd8b2 Mon Sep 17 00:00:00 2001 From: gsgrattan Date: Tue, 5 Nov 2024 12:40:27 -0700 Subject: [PATCH 17/35] Integrated new MetaData dataclass objects into python notebooks --- notebooks/DickeModelExample.ipynb | 191 +++++----- notebooks/ExoticPhasesExample.ipynb | 169 ++++----- ...HighTemperatureSuperConductorExample.ipynb | 212 ++++++----- notebooks/MagneticLattices.ipynb | 330 ++++++++++-------- notebooks/PhotosynthesisExample.ipynb | 316 +++++++++-------- notebooks/RuClExample.ipynb | 96 +++-- 6 files changed, 725 insertions(+), 589 deletions(-) diff --git a/notebooks/DickeModelExample.ipynb b/notebooks/DickeModelExample.ipynb index d355d1e..f6d7abf 100644 --- a/notebooks/DickeModelExample.ipynb +++ b/notebooks/DickeModelExample.ipynb @@ -37,17 +37,26 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 1, "metadata": { "tags": [] }, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/gsgrattan/.conda/envs/qc-apps/lib/python3.11/site-packages/cotengra/hyperoptimizers/hyper.py:33: UserWarning: Couldn't import `kahypar` - skipping from default hyper optimizer and using basic `labels` method instead.\n", + " warnings.warn(\n" + ] + } + ], "source": [ "import time\n", "import numpy as np\n", "from networkx import get_node_attributes, draw\n", "from qca.utils.algo_utils import gsee_resource_estimation\n", - "from qca.utils.utils import EstimateMetaData\n", + "from qca.utils.utils import GSEEMetaData\n", "from qca.utils.hamiltonian_utils import (\n", " generate_dicke_model_nx, dicke_model_qubit_hamiltonian, tavis_cummings_model_qubit_hamiltonian,\n", " bosonic_annihilation_operator, bosonic_creation_operator, bosonic_number_operator)" @@ -55,7 +64,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 2, "metadata": { "tags": [] }, @@ -144,7 +153,7 @@ }, { "data": { - "image/png": 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", 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", 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" ] @@ -220,7 +229,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 3, "metadata": { "tags": [] }, @@ -239,7 +248,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 4, "metadata": { "tags": [] }, @@ -253,6 +262,8 @@ } ], "source": [ + "name = 'DickieModel'\n", + "\n", "#defining parameters\n", "n_s = 10 #using 10 instead of 100 for runtime\n", "n_b = 10 #using 10 instead of 100 for runtime\n", @@ -274,6 +285,9 @@ "#this scales the circuit depth proportional to 2 ^ bits_precision\n", "bits_precision_dicke = 10\n", "\n", + "#This determines if we want to extrapolate our RE or want to calculate it explicitly\n", + "extrapolate = True\n", + "\n", "E_min_dicke = -len(ham_dicke.terms)\n", "E_max_dicke = 0\n", "dicke_omega = E_max_dicke-E_min_dicke\n", @@ -295,16 +309,24 @@ "total_value = 0\n", "repetitions = 1\n", "value_per_circuit=total_value / repetitions\n", - "dicke_metadata = EstimateMetaData(\n", - " id=time.time_ns(),\n", - " name='DickeModel',\n", - " category='scientific',\n", - " size=f'{n_b} + 1 + {n_s}',\n", - " task='Ground State Energy Estimation',\n", - " implementations=f'GSEE, evolution_time={t_dicke}, bits_precision={bits_precision_dicke}, trotter_order={trotter_order_dicke}, n_s={n_s}, n_b={n_b}',\n", - " value_per_circuit=value_per_circuit,\n", - " repetitions_per_application=repetitions\n", - ")" + "\n", + "\n", + "dicke_metadata = GSEEMetaData(\n", + " id=time.time_ns(),\n", + " name=name,\n", + " category='scientific',\n", + " size=f'{n_b} + 1 + {n_s}',\n", + " task='Ground State Energy Estimation',\n", + " value_per_circuit=value_per_circuit,\n", + " repetitions_per_application=repetitions,\n", + "\n", + " evolution_time=t_dicke,\n", + " trotter_order = trotter_order_dicke,\n", + " is_extrapolated=extrapolate,\n", + " bits_precision = bits_precision_dicke,\n", + " nsteps=trotter_steps_dicke,\n", + " implementation='GSEE'\n", + " )" ] }, { @@ -316,7 +338,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 5, "metadata": { "tags": [] }, @@ -326,36 +348,38 @@ "output_type": "stream", "text": [ "Estimating Dicke\n", - "Time to generate circuit for GSEE: 4.2208004742860794e-05 seconds\n", - " Time to decompose high level HPowGate circuit: 8.612498641014099e-05 seconds \n", - " Time to transform decomposed HPowGate circuit to Clifford+T: 0.00018929201178252697 seconds\n", - " Time to decompose high level IdentityGate circuit: 1.3249926269054413e-05 seconds \n", - " Time to transform decomposed IdentityGate circuit to Clifford+T: 3.2499665394425392e-06 seconds\n", - " Time to decompose high level PhaseOffset circuit: 7.433409336954355e-05 seconds \n", - " Time to transform decomposed PhaseOffset circuit to Clifford+T: 7.695797830820084e-05 seconds\n", - " Time to decompose high level Trotter_Unitary circuit: 0.4055276250001043 seconds \n", - " Time to transform decomposed Trotter_Unitary circuit to Clifford+T: 3.4485969999805093 seconds\n", - " Time to decompose high level MeasurementGate circuit: 0.001431209035217762 seconds \n", - " Time to transform decomposed MeasurementGate circuit to Clifford+T: 5.054206121712923e-05 seconds\n", - "Time to estimate dicke: 6.783997792052105\n" + "Time to generate circuit for GSEE: 0.00022629095474258065 seconds\n", + " Time to decompose high level HPowGate circuit: 0.0007019999902695417 seconds \n", + " Time to transform decomposed HPowGate circuit to Clifford+T: 0.0005076670204289258 seconds\n", + " Time to decompose high level IdentityGate circuit: 1.4999997802078724e-05 seconds \n", + " Time to transform decomposed IdentityGate circuit to Clifford+T: 8.875038474798203e-06 seconds\n", + " Time to decompose high level PhaseOffset circuit: 8.595798863098025e-05 seconds \n", + " Time to transform decomposed PhaseOffset circuit to Clifford+T: 0.00010587502038106322 seconds\n", + " Time to decompose high level Trotter_Unitary circuit: 0.5343438750132918 seconds \n", + " Time to transform decomposed Trotter_Unitary circuit to Clifford+T: 3.6690024160197936 seconds\n", + " Time to decompose high level MeasurementGate circuit: 0.0013707500183954835 seconds \n", + " Time to transform decomposed MeasurementGate circuit to Clifford+T: 5.0333968829363585e-05 seconds\n", + "Time to estimate dicke: 7.14005545899272\n" ] } ], "source": [ "print('Estimating Dicke')\n", "t0 = time.perf_counter()\n", + "\n", "estimate = gsee_resource_estimation(\n", - " outdir='GSE/DickeModel/',\n", - " numsteps=trotter_steps_dicke,\n", - " gsee_args=args_dicke,\n", - " init_state=init_state_dicke,\n", - " precision_order=1, #actual precision bits accounted as scaling factors in the resource estimate\n", - " phase_offset=dicke_phase_offset,\n", - " bits_precision=bits_precision_dicke,\n", - " circuit_name='DickeModelExample',\n", - " metadata = dicke_metadata,\n", - " write_circuits=True\n", - ")\n", + " outdir='GSE/DickeModel/',\n", + " nsteps=trotter_steps_dicke,\n", + " gsee_args=args_dicke,\n", + " init_state=init_state_dicke,\n", + " precision_order=1, #actual precision bits accounted as scaling factors in the resource estimate\n", + " phase_offset=dicke_phase_offset,\n", + " bits_precision=bits_precision_dicke,\n", + " circuit_name=name,\n", + " is_extrapolated = extrapolate,\n", + " metadata = dicke_metadata,\n", + " write_circuits=True\n", + " )\n", "t1 = time.perf_counter()\n", "print(f'Time to estimate dicke: {t1-t0}')" ] @@ -376,7 +400,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 6, "metadata": { "tags": [] }, @@ -395,21 +419,14 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 7, "metadata": { "tags": [] }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "starting\n" - ] - } - ], + "outputs": [], "source": [ + "name='TavisCummingsModel'\n", + "\n", "#defining parameters\n", "n_s = 10 #using 10 instead of 100 for runtime\n", "n_b = 10 #using 10 instead of 100 for runtime\n", @@ -425,6 +442,9 @@ "#this scales the circuit depth proportional to 2 ^ bits_precision\n", "bits_precision_tavis_cummings = 10\n", "\n", + "#This determines if we want to extrapolate our RE or want to calculate it explicitly\n", + "extrapolate = True\n", + "\n", "E_min_tavis_cummings = -len(ham_tavis_cummings.terms)\n", "E_max_tavis_cummings = 0\n", "tavis_cummings_omega = E_max_tavis_cummings-E_min_tavis_cummings\n", @@ -442,19 +462,23 @@ "\n", "init_state_tavis_cummings = [0] * (n_b + n_s + 1) #TODO: use Fock state from Hartree-Fock as initial state\n", "\n", - "print('starting')\n", - "total_value = 0\n", - "repetitions = 1\n", - "value_per_circuit=total_value / repetitions\n", - "tavis_cummings_metadata = EstimateMetaData(\n", + "\n", + "tavis_cummings_metadata = GSEEMetaData(\n", " id=time.time_ns(),\n", - " name='TavisCummingsModel',\n", + " name=name,\n", " category='scientific',\n", " size=f'{n_b} + 1 + {n_s}',\n", " task='Ground State Energy Estimation',\n", - " implementations=f'GSEE, evolution_time={t_tavis_cummings}, bits_precision={bits_precision_tavis_cummings}, trotter_order={trotter_order_tavis_cummings}, n_s={n_s}, n_b={n_b}',\n", " value_per_circuit=value_per_circuit,\n", - " repetitions_per_application=repetitions\n", + " repetitions_per_application=repetitions,\n", + "\n", + " \n", + " evolution_time=t_tavis_cummings,\n", + " trotter_order = trotter_order_tavis_cummings,\n", + " is_extrapolated=extrapolate,\n", + " bits_precision = bits_precision_tavis_cummings,\n", + " nsteps=trotter_steps_tavis_cummings,\n", + " implementation='GSEE'\n", ")" ] }, @@ -467,7 +491,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 8, "metadata": { "tags": [] }, @@ -477,51 +501,46 @@ "output_type": "stream", "text": [ "Estimating tavis_cummings\n", - "Time to generate circuit for GSEE: 4.183291457593441e-05 seconds\n", - " Time to decompose high level HPowGate circuit: 8.395896293222904e-05 seconds \n", - " Time to transform decomposed HPowGate circuit to Clifford+T: 0.00019545794930309057 seconds\n", - " Time to decompose high level IdentityGate circuit: 1.2749922461807728e-05 seconds \n", - " Time to transform decomposed IdentityGate circuit to Clifford+T: 3.832974471151829e-06 seconds\n", - " Time to decompose high level PhaseOffset circuit: 7.833307608962059e-05 seconds \n", - " Time to transform decomposed PhaseOffset circuit to Clifford+T: 8.67500202730298e-05 seconds\n", - " Time to decompose high level Trotter_Unitary circuit: 0.7705561659531668 seconds \n", - " Time to transform decomposed Trotter_Unitary circuit to Clifford+T: 4.374742791987956 seconds\n", - " Time to decompose high level MeasurementGate circuit: 0.0025906249647960067 seconds \n", - " Time to transform decomposed MeasurementGate circuit to Clifford+T: 5.0582922995090485e-05 seconds\n", - "Time to estimate tavis_cummings: 10.892113291076384\n" + "Time to generate circuit for GSEE: 4.600000102072954e-05 seconds\n", + " Time to decompose high level HPowGate circuit: 0.00013637501979246736 seconds \n", + " Time to transform decomposed HPowGate circuit to Clifford+T: 0.00018408300820738077 seconds\n", + " Time to decompose high level IdentityGate circuit: 1.4625024050474167e-05 seconds \n", + " Time to transform decomposed IdentityGate circuit to Clifford+T: 4.708010237663984e-06 seconds\n", + " Time to decompose high level PhaseOffset circuit: 8.475000504404306e-05 seconds \n", + " Time to transform decomposed PhaseOffset circuit to Clifford+T: 8.1458012573421e-05 seconds\n", + " Time to decompose high level Trotter_Unitary circuit: 0.8101094159646891 seconds \n", + " Time to transform decomposed Trotter_Unitary circuit to Clifford+T: 4.786060957994778 seconds\n", + " Time to decompose high level MeasurementGate circuit: 0.002639999962411821 seconds \n", + " Time to transform decomposed MeasurementGate circuit to Clifford+T: 6.304198177531362e-05 seconds\n", + "Time to estimate tavis_cummings: 11.428455667046364\n" ] } ], "source": [ "print('Estimating tavis_cummings')\n", "t0 = time.perf_counter()\n", + "\n", "estimate = gsee_resource_estimation(\n", " outdir='GSE/TavisCummings/',\n", - " numsteps=trotter_steps_tavis_cummings,\n", + " nsteps=trotter_steps_tavis_cummings,\n", " gsee_args=args_tavis_cummings,\n", " init_state=init_state_tavis_cummings,\n", " precision_order=1, #actual precision bits accounted as scaling factors in the resource estimate\n", " phase_offset=tavis_cummings_phase_offset,\n", " bits_precision=bits_precision_tavis_cummings,\n", - " circuit_name='TavisCummingsModelExample',\n", + " circuit_name=name,\n", " metadata = tavis_cummings_metadata,\n", + " is_extrapolated=extrapolate,\n", " write_circuits=True\n", - ")\n", + " )\n", "t1 = time.perf_counter()\n", "print(f'Time to estimate tavis_cummings: {t1-t0}')" ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { "kernelspec": { - "display_name": "other_qca", + "display_name": "qc-apps", "language": "python", "name": "python3" }, @@ -535,7 +554,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.9" + "version": "3.11.10" } }, "nbformat": 4, diff --git a/notebooks/ExoticPhasesExample.ipynb b/notebooks/ExoticPhasesExample.ipynb index a1d8961..6a1c4f3 100644 --- a/notebooks/ExoticPhasesExample.ipynb +++ b/notebooks/ExoticPhasesExample.ipynb @@ -53,9 +53,18 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 1, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/gsgrattan/.conda/envs/qc-apps/lib/python3.11/site-packages/cotengra/hyperoptimizers/hyper.py:33: UserWarning: Couldn't import `kahypar` - skipping from default hyper optimizer and using basic `labels` method instead.\n", + " warnings.warn(\n" + ] + } + ], "source": [ "import time\n", "\n", @@ -92,7 +101,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -125,12 +134,12 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 3, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -174,7 +183,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 4, "metadata": {}, "outputs": [], "source": [ @@ -199,55 +208,55 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "{((0, 0), (1, 0)): Text(-0.19514009082261508, 0.6927395549709421, '1'),\n", - " ((0, 0), (0, 1)): Text(0.13704481065734653, 0.7056984923842029, '1'),\n", - " ((0, 0), (1, 1)): Text(-0.023774917341547352, 0.5674300331167816, '0.125'),\n", - " ((0, 1), (1, 1)): Text(0.14801415826468878, 0.44419012659627377, '1'),\n", - " ((0, 1), (0, 2)): Text(0.49439046242799756, 0.43752716884539544, '1'),\n", - " ((0, 1), (1, 2)): Text(0.3380274340978031, 0.2983792170019366, '0.125'),\n", - " ((0, 2), (1, 2)): Text(0.5235878988807918, 0.15345749781423823, '1'),\n", - " ((0, 2), (0, 3)): Text(0.8399786243224898, 0.16643636561393982, '1'),\n", - " ((0, 2), (1, 3)): Text(0.6917150323020449, 0.02726937369585114, 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", 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", 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" ] @@ -293,7 +302,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ @@ -309,7 +318,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 7, "metadata": {}, "outputs": [], "source": [ @@ -345,7 +354,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 8, "metadata": {}, "outputs": [ { @@ -353,18 +362,18 @@ "output_type": "stream", "text": [ "Estimating Heisenberg king graph of size 5\n", - "Time to generate circuit for GSEE: 6.279104854911566e-05 seconds\n", - " Time to decompose high level HPowGate circuit: 8.887494914233685e-05 seconds \n", - " Time to transform decomposed HPowGate circuit to Clifford+T: 0.0003006670158356428 seconds\n", - " Time to decompose high level IdentityGate circuit: 1.6708974726498127e-05 seconds \n", - " Time to transform decomposed IdentityGate circuit to Clifford+T: 4.375004209578037e-06 seconds\n", - " Time to decompose high level PhaseOffset circuit: 0.00012099999003112316 seconds \n", - " Time to transform decomposed PhaseOffset circuit to Clifford+T: 9.816605597734451e-05 seconds\n", - " Time to decompose high level Trotter_Unitary circuit: 0.08363029104657471 seconds \n", - " Time to transform decomposed Trotter_Unitary circuit to Clifford+T: 0.6958530839765444 seconds\n", - " Time to decompose high level MeasurementGate circuit: 0.000298250000923872 seconds \n", - " Time to transform decomposed MeasurementGate circuit to Clifford+T: 3.8874917663633823e-05 seconds\n", - "Time to estimate Heisenberg king graph: 1.5609900000272319\n" + "Time to generate circuit for GSEE: 0.00012874999083578587 seconds\n", + " Time to decompose high level HPowGate circuit: 0.0002209999947808683 seconds \n", + " Time to transform decomposed HPowGate circuit to Clifford+T: 0.00048525002785027027 seconds\n", + " Time to decompose high level IdentityGate circuit: 1.2708944268524647e-05 seconds \n", + " Time to transform decomposed IdentityGate circuit to Clifford+T: 8.083006832748652e-06 seconds\n", + " Time to decompose high level PhaseOffset circuit: 7.633399218320847e-05 seconds \n", + " Time to transform decomposed PhaseOffset circuit to Clifford+T: 8.433300536125898e-05 seconds\n", + " Time to decompose high level Trotter_Unitary circuit: 0.08183891698718071 seconds \n", + " Time to transform decomposed Trotter_Unitary circuit to Clifford+T: 0.9530299159814604 seconds\n", + " Time to decompose high level MeasurementGate circuit: 0.00023866700939834118 seconds \n", + " Time to transform decomposed MeasurementGate circuit to Clifford+T: 4.804198397323489e-05 seconds\n", + "Time to estimate Heisenberg king graph: 1.811745457991492\n" ] } ], @@ -373,7 +382,7 @@ "t0 = time.perf_counter()\n", "gsee_resource_estimation(\n", " outdir='GSE/Heisenberg_GSEE/Square/',\n", - " numsteps=trotter_steps,\n", + " nsteps=trotter_steps,\n", " gsee_args=gsee_args,\n", " init_state=init_state,\n", " precision_order=1,\n", @@ -395,7 +404,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 9, "metadata": {}, "outputs": [], "source": [ @@ -427,7 +436,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 11, "metadata": {}, "outputs": [ { @@ -435,18 +444,18 @@ "output_type": "stream", "text": [ "Estimating Heisenberg model on a triangular lattice of size 8\n", - "Time to generate circuit for GSEE: 0.00012920796871185303 seconds\n", - " Time to decompose high level HPowGate circuit: 8.074997458606958e-05 seconds \n", - " Time to transform decomposed HPowGate circuit to Clifford+T: 0.0002009579911828041 seconds\n", - " Time to decompose high level IdentityGate circuit: 1.5167053788900375e-05 seconds \n", - " Time to transform decomposed IdentityGate circuit to Clifford+T: 3.7919962778687477e-06 seconds\n", - " Time to decompose high level PhaseOffset circuit: 8.162495214492083e-05 seconds \n", - " Time to transform decomposed PhaseOffset circuit to Clifford+T: 8.74160323292017e-05 seconds\n", - " Time to decompose high level Trotter_Unitary circuit: 0.1786704579135403 seconds \n", - " Time to transform decomposed Trotter_Unitary circuit to Clifford+T: 2.3817522500175983 seconds\n", - " Time to decompose high level MeasurementGate circuit: 0.0005746250972151756 seconds \n", - " Time to transform decomposed MeasurementGate circuit to Clifford+T: 4.39999857917428e-05 seconds\n", - "Time to estimate Heisenberg on a triangular lattice: 4.330899374908768\n" + "Time to generate circuit for GSEE: 0.00017570896307006478 seconds\n", + " Time to decompose high level HPowGate circuit: 0.00014104199362918735 seconds \n", + " Time to transform decomposed HPowGate circuit to Clifford+T: 0.000512166996486485 seconds\n", + " Time to decompose high level IdentityGate circuit: 1.5666999388486147e-05 seconds \n", + " Time to transform decomposed IdentityGate circuit to Clifford+T: 4.499976057559252e-06 seconds\n", + " Time to decompose high level PhaseOffset circuit: 0.00010674999793991446 seconds \n", + " Time to transform decomposed PhaseOffset circuit to Clifford+T: 0.00011670798994600773 seconds\n", + " Time to decompose high level Trotter_Unitary circuit: 0.18287804099963978 seconds \n", + " Time to transform decomposed Trotter_Unitary circuit to Clifford+T: 2.748462792020291 seconds\n", + " Time to decompose high level MeasurementGate circuit: 0.00045704201329499483 seconds \n", + " Time to transform decomposed MeasurementGate circuit to Clifford+T: 4.191702464595437e-05 seconds\n", + "Time to estimate Heisenberg on a triangular lattice: 4.639010249986313\n" ] } ], @@ -455,7 +464,7 @@ "t0 = time.perf_counter()\n", "gsee_resource_estimation(\n", " outdir='GSE/Heisenberg_GSEE/Triangular/',\n", - " numsteps=triangular_trotter_steps,\n", + " nsteps=triangular_trotter_steps,\n", " gsee_args=gsee_args,\n", " init_state=init_state,\n", " precision_order=1,\n", @@ -506,7 +515,7 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 12, "metadata": {}, "outputs": [], "source": [ @@ -517,16 +526,16 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 13, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Time to find term ordering: 0.0012380409752950072 seconds\n", - "Time to generate trotter circuit from openfermion: 1.0420335456728935e-06 seconds\n", - "Time to generate a clifford + T circuit from trotter circuit: 0.7697882909560576 seconds\n" + "Time to find term ordering: 0.0030372500186786056 seconds\n", + "Time to generate trotter circuit from openfermion: 2.167013008147478e-06 seconds\n", + "Time to generate a clifford + T circuit from trotter circuit: 0.8448652499937452 seconds\n" ] } ], @@ -552,7 +561,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3 (ipykernel)", + "display_name": "qc-apps", "language": "python", "name": "python3" }, @@ -566,7 +575,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.9" + "version": "3.11.10" } }, "nbformat": 4, diff --git a/notebooks/HighTemperatureSuperConductorExample.ipynb b/notebooks/HighTemperatureSuperConductorExample.ipynb index 07479b2..e420ff6 100644 --- a/notebooks/HighTemperatureSuperConductorExample.ipynb +++ b/notebooks/HighTemperatureSuperConductorExample.ipynb @@ -59,7 +59,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "/Users/jonhas/anaconda3/envs/other/lib/python3.12/site-packages/cotengra/hyperoptimizers/hyper.py:33: UserWarning: Couldn't import `kahypar` - skipping from default hyper optimizer and using basic `labels` method instead.\n", + "/Users/gsgrattan/.conda/envs/qc-apps/lib/python3.11/site-packages/cotengra/hyperoptimizers/hyper.py:33: UserWarning: Couldn't import `kahypar` - skipping from default hyper optimizer and using basic `labels` method instead.\n", " warnings.warn(\n" ] } @@ -73,7 +73,7 @@ "\n", "from networkx import get_node_attributes, draw, draw_networkx_edge_labels\n", "\n", - "from qca.utils.utils import EstimateMetaData\n", + "from qca.utils.utils import GSEEMetaData \n", "from qca.utils.algo_utils import gsee_resource_estimation\n", "from qca.utils.hamiltonian_utils import (generate_two_orbital_nx, nx_to_two_orbital_hamiltonian,\n", " generate_three_orbital_nx, nx_to_three_orbital_hamiltonian)" @@ -137,6 +137,9 @@ "#this scales the circuit depth proportional to 2 ^ bits_precision\n", "bits_precision_one_band = 16\n", "\n", + "#This determines if we want to extrapolate our RE or want to calculate it explicitly\n", + "extrapolate = True\n", + "\n", "E_min_one_band = -len(ham_one_band.terms)\n", "E_max_one_band = 0\n", "one_band_omega = E_max_one_band-E_min_one_band\n", @@ -154,13 +157,19 @@ "\n", "init_state_one_band = [0] * n * n * 2 #TODO: use Fock state from Hartree-Fock as initial state\n", "\n", - "one_band_metadata = EstimateMetaData(\n", + "one_band_metadata = GSEEMetaData(\n", " id=2000,\n", " name='FermiHubbard_One_Band',\n", " category='scientific',\n", " size=f'{n}x{n}',\n", " task='Ground State Energy Estimation',\n", - " implementations=f'GSEE, evolution_time={t_one_band}, bits_precision={bits_precision_one_band}, trotter_order={trotter_order_one_band}',\n", + "\n", + " evolution_time=t_one_band,\n", + " trotter_order=trotter_order_one_band,\n", + " is_extrapolated=extrapolate,\n", + " bits_precision=bits_precision_one_band,\n", + " nsteps=trotter_steps_one_band,\n", + " implementation=\"GSEE\"\n", ")" ] }, @@ -183,18 +192,18 @@ "output_type": "stream", "text": [ "Estimating one_band\n", - "Time to generate circuit for GSEE: 7.10420008545043e-05 seconds\n", - " Time to decompose high level HPowGate circuit: 0.00018562500008556526 seconds \n", - " Time to transform decomposed HPowGate circuit to Clifford+T: 0.0005207089998293668 seconds\n", - " Time to decompose high level IdentityGate circuit: 1.5208001059363596e-05 seconds \n", - " Time to transform decomposed IdentityGate circuit to Clifford+T: 4.667001121561043e-06 seconds\n", - " Time to decompose high level PhaseOffset circuit: 8.129200068651699e-05 seconds \n", - " Time to transform decomposed PhaseOffset circuit to Clifford+T: 9.4541001089965e-05 seconds\n", - " Time to decompose high level Trotter_Unitary circuit: 0.04967725000096834 seconds \n", - " Time to transform decomposed Trotter_Unitary circuit to Clifford+T: 0.4006794169999921 seconds\n", - " Time to decompose high level MeasurementGate circuit: 0.00022004200036462862 seconds \n", - " Time to transform decomposed MeasurementGate circuit to Clifford+T: 7.874999937484972e-05 seconds\n", - "Time to estimate one_band: 0.8638855830013199\n" + "Time to generate circuit for GSEE: 7.358298171311617e-05 seconds\n", + " Time to decompose high level HPowGate circuit: 0.0002579170395620167 seconds \n", + " Time to transform decomposed HPowGate circuit to Clifford+T: 0.00040374998934566975 seconds\n", + " Time to decompose high level IdentityGate circuit: 2.0458013750612736e-05 seconds \n", + " Time to transform decomposed IdentityGate circuit to Clifford+T: 9.665964171290398e-06 seconds\n", + " Time to decompose high level PhaseOffset circuit: 9.662494994699955e-05 seconds \n", + " Time to transform decomposed PhaseOffset circuit to Clifford+T: 0.0001105000264942646 seconds\n", + " Time to decompose high level Trotter_Unitary circuit: 0.0451331670046784 seconds \n", + " Time to transform decomposed Trotter_Unitary circuit to Clifford+T: 0.3732286249869503 seconds\n", + " Time to decompose high level MeasurementGate circuit: 0.0001948749995790422 seconds \n", + " Time to transform decomposed MeasurementGate circuit to Clifford+T: 3.7833990063518286e-05 seconds\n", + "Time to estimate one_band: 0.7837549999821931\n" ] } ], @@ -203,13 +212,14 @@ "t0 = time.perf_counter()\n", "gsee_resource_estimation(\n", " outdir='GSE/FermiHubbard/',\n", - " numsteps=trotter_steps_one_band,\n", + " nsteps=trotter_steps_one_band,\n", " gsee_args=args_one_band,\n", " init_state=init_state_one_band,\n", " precision_order=1,\n", " bits_precision=bits_precision_one_band,\n", " phase_offset=one_band_phase_offset,\n", " circuit_name='one_band',\n", + " is_extrapolated=extrapolate,\n", " metadata=one_band_metadata,\n", " write_circuits=True\n", ")\n", @@ -271,7 +281,7 @@ }, { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -461,6 +471,9 @@ "bits_precision_ideal = 16\n", "bits_precision_current_limit = 16\n", "\n", + "#This determines if we want to extrapolate our RE or want to calculate it explicitly\n", + "extrapolate = True\n", + "\n", "E_min_ideal = -len(ham_ideal.terms)\n", "E_max_ideal = 0\n", "omega_ideal = E_max_ideal-E_min_ideal\n", @@ -501,22 +514,33 @@ }, "outputs": [], "source": [ - "metadata_current_limit = EstimateMetaData(\n", + "metadata_current_limit = GSEEMetaData(\n", " id=3000,\n", " name='FermiHubbard_Two_Band_Current_Limit`',\n", " category='scientific',\n", " size=f'{6}x{7}',\n", " task='Ground State Energy Estimation',\n", - " implementations=f'GSEE, evolution_time={t_current_limit}, bits_precision={bits_precision_current_limit}, trotter_order={trotter_order_current_limit}',\n", + "\n", + " evolution_time=t_current_limit,\n", + " trotter_order=trotter_order_current_limit,\n", + " is_extrapolated=extrapolate,\n", + " bits_precision=bits_precision_current_limit,\n", + " nsteps=trotter_steps_current_limit,\n", + " implementation=\"GSEE\"\n", ")\n", "\n", - "metadata_ideal = EstimateMetaData(\n", + "metadata_ideal = GSEEMetaData(\n", " id=4000,\n", " name='FermiHubbard_Two_Band_Ideal',\n", " category='scientific',\n", " size=f'{20}x{20}',\n", " task='Ground State Energy Estimation',\n", - " implementations=f'GSEE, evolution_time={t_ideal}, bits_precision={bits_precision_ideal}, trotter_order={trotter_order_ideal}',\n", + " evolution_time=t_ideal,\n", + " trotter_order=trotter_order_ideal,\n", + " is_extrapolated=extrapolate,\n", + " bits_precision=bits_precision_ideal,\n", + " nsteps=trotter_steps_ideal,\n", + " implementation=\"GSEE\"\n", ")" ] }, @@ -530,31 +554,31 @@ "output_type": "stream", "text": [ "Estimating Current Limit\n", - "Time to generate circuit for GSEE: 4.112499846087303e-05 seconds\n", - " Time to decompose high level HPowGate circuit: 0.00010516700058360584 seconds \n", - " Time to transform decomposed HPowGate circuit to Clifford+T: 0.00019879199862771202 seconds\n", - " Time to decompose high level IdentityGate circuit: 3.52080005541211e-05 seconds \n", - " Time to transform decomposed IdentityGate circuit to Clifford+T: 5.6249991757795215e-06 seconds\n", - " Time to decompose high level PhaseOffset circuit: 9.079200026462786e-05 seconds \n", - " Time to transform decomposed PhaseOffset circuit to Clifford+T: 8.262499977718107e-05 seconds\n", - " Time to decompose high level Trotter_Unitary circuit: 0.22323074999985693 seconds \n", - " Time to transform decomposed Trotter_Unitary circuit to Clifford+T: 1.060906791999514 seconds\n", - " Time to decompose high level MeasurementGate circuit: 0.0008073329991020728 seconds \n", - " Time to transform decomposed MeasurementGate circuit to Clifford+T: 4.454199915926438e-05 seconds\n", - "Time to estimate Current Limit: 2.584240915999544\n", + "Time to generate circuit for GSEE: 9.895797120407224e-05 seconds\n", + " Time to decompose high level HPowGate circuit: 0.0002941249986179173 seconds \n", + " Time to transform decomposed HPowGate circuit to Clifford+T: 0.0009380419505760074 seconds\n", + " Time to decompose high level IdentityGate circuit: 1.6625039279460907e-05 seconds \n", + " Time to transform decomposed IdentityGate circuit to Clifford+T: 4.499976057559252e-06 seconds\n", + " Time to decompose high level PhaseOffset circuit: 8.404103573411703e-05 seconds \n", + " Time to transform decomposed PhaseOffset circuit to Clifford+T: 0.00010008300887420774 seconds\n", + " Time to decompose high level Trotter_Unitary circuit: 0.25881625001784414 seconds \n", + " Time to transform decomposed Trotter_Unitary circuit to Clifford+T: 0.9029138330370188 seconds\n", + " Time to decompose high level MeasurementGate circuit: 0.001000499993097037 seconds \n", + " Time to transform decomposed MeasurementGate circuit to Clifford+T: 4.299997817724943e-05 seconds\n", + "Time to estimate Current Limit: 2.4191256249905564\n", "Estimating Ideal\n", - "Time to generate circuit for GSEE: 3.574999936972745e-05 seconds\n", - " Time to decompose high level HPowGate circuit: 0.00010112500058312435 seconds \n", - " Time to transform decomposed HPowGate circuit to Clifford+T: 9.445900104765315e-05 seconds\n", - " Time to decompose high level IdentityGate circuit: 1.5125000572879799e-05 seconds \n", - " Time to transform decomposed IdentityGate circuit to Clifford+T: 4.249999619787559e-06 seconds\n", - " Time to decompose high level PhaseOffset circuit: 7.337500028370414e-05 seconds \n", - " Time to transform decomposed PhaseOffset circuit to Clifford+T: 3.854200076602865e-05 seconds\n", - " Time to decompose high level Trotter_Unitary circuit: 0.27389312500054075 seconds \n", - " Time to transform decomposed Trotter_Unitary circuit to Clifford+T: 0.7673925409999356 seconds\n", - " Time to decompose high level MeasurementGate circuit: 0.0009456249990762444 seconds \n", - " Time to transform decomposed MeasurementGate circuit to Clifford+T: 8.712499948160257e-05 seconds\n", - "Time to estimate Ideal: 2.727386500000648\n" + "Time to generate circuit for GSEE: 3.4584023524075747e-05 seconds\n", + " Time to decompose high level HPowGate circuit: 6.941700121387839e-05 seconds \n", + " Time to transform decomposed HPowGate circuit to Clifford+T: 9.016698459163308e-05 seconds\n", + " Time to decompose high level IdentityGate circuit: 1.0707997716963291e-05 seconds \n", + " Time to transform decomposed IdentityGate circuit to Clifford+T: 3.5830307751893997e-06 seconds\n", + " Time to decompose high level PhaseOffset circuit: 7.508299313485622e-05 seconds \n", + " Time to transform decomposed PhaseOffset circuit to Clifford+T: 3.8833997678011656e-05 seconds\n", + " Time to decompose high level Trotter_Unitary circuit: 0.27210870798444375 seconds \n", + " Time to transform decomposed Trotter_Unitary circuit to Clifford+T: 0.6658007500227541 seconds\n", + " Time to decompose high level MeasurementGate circuit: 0.0008316660532727838 seconds \n", + " Time to transform decomposed MeasurementGate circuit to Clifford+T: 4.2208004742860794e-05 seconds\n", + "Time to estimate Ideal: 2.424980083014816\n" ] } ], @@ -564,13 +588,14 @@ "\n", "estimate_current_limit = gsee_resource_estimation(\n", " outdir='GSE/FermiHubbard/',\n", - " numsteps=trotter_steps_current_limit,\n", + " nsteps=trotter_steps_current_limit,\n", " gsee_args=current_limit_args,\n", " init_state=init_state_current_limit,\n", " precision_order=1,\n", " bits_precision=bits_precision_current_limit,\n", " phase_offset=phase_offset_current_limit,\n", " circuit_name='two_band_current_limit',\n", + " is_extrapolated=extrapolate,\n", " metadata=metadata_current_limit,\n", " write_circuits=True\n", ")\n", @@ -581,13 +606,14 @@ "t0 = time.perf_counter()\n", "estimate_ideal = gsee_resource_estimation(\n", " outdir='GSE/FermiHubbard/',\n", - " numsteps=trotter_steps_ideal,\n", + " nsteps=trotter_steps_ideal,\n", " gsee_args=ideal_args,\n", " init_state=init_state_ideal,\n", " precision_order=1,\n", " bits_precision=bits_precision_ideal,\n", " phase_offset=phase_offset_ideal,\n", " circuit_name='two_band_ideal',\n", + " is_extrapolated=extrapolate,\n", " metadata=metadata_ideal,\n", " write_circuits=True\n", ")\n", @@ -685,7 +711,7 @@ }, { "data": { - "image/png": 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xghYtWkSGhoaUm5ur0nqVITc3l4yMjGjjxo38/SIgIIAXk0RqnIuchCoL0+hR7HlasWIF3bhxg5o3b04eHh60Y8cO5npSRklOTqadO3eSv78/Va9enezt7Wn06NH0/PlzGjlyJEVGRtL79+/pxIkTNHnyZKpSpQrNnTuXbG1taciQIWRlZUUnTpyg48eP08Xj+ynzyTUSqniXMu+a+DUgkUjo6tWr1Lp1a1q0aBG1aNGC9u3bR+fOnaNx48ZRQkIC7duySu364Vvkm92hJCJ69i6D2oWcpWwVhufragnp5M+tqGoxvmFisZiioqIoIiKCjh8/To8ePVJZ/epCHX2lJQB92vsLZb55RsuWLaOhQ4fKvBuSlpZGZ8+e/exQfvIk3b59m4iI6tatS56enuTp6UmtWrWicuXKqay9DNXx77//kp+fH92+fZvGTJ1NxwQN1T4Pnz17RitXrqR169ZRamoqde/enXbt2kVaWlqlvgsHgADIlGRdHXNRRBJ6vm4k1a5qSZs2bSIXFxc6fvw4hYaG0okTJ8jKyopGjx5NI0aMUDoBNUNx8t73Tp06Rbdu3SKiku97169fp+XLl9OOHTtIS0uLhgwZQuPGjSMHBwfatGkTjR8/ngwMDGhuyGpafFtX42tiWQIAXbx4kUaNGkVxcXHk5OREQUFBNGDAgHw5a0tLP3zNfNOCkoho95VEmrrvpsrKW+Rbj/q428h8vUQioYyMDDIyMtLIogaAbty4QeXLly82yrww1NFXXjWNaPz48fT777+Tl5cXrV+/nmxtbeUuKzk5mU6fPs3faBMSEkgkEpGHhwd/o23SpAnp6uqqrP0M+cnKyqLg4GBavHgx1a1blzZv3kyurq4anYefPn2irVu30vLlyyk8PJzatWtX6oJSXtTRXw5ab2no0KF069YtmjJlCs2YMYP09PTo9u3btHz5ctq2bRsREQ0cOJACAwOpbt26KqufUTjZ2dl04cIFOnnyJJ06dYquXLlCEomEbG1t+fta27ZtC02oL5FI6MiRIxQaGkqRkZFUtWpVGjt2LA0bNoxMTEzo6dOnFBAQQCdPnqQhQ4bQsmXLyMTEpFTXRABlYi7Wrl2batasSUFBQeTp6Vlkm0pbP3xtfPOCkohoReQDWnrivuIFAEQCAU1q70ij29iVfH0pIRWv9vb29OrVK6pQoQI5OzvnS2VUp06dIo+OIyIau+YIHUog+pzsRfGJ/2VfHTt2jIYPH04fPnygRYsW0ciRIxU+Eg8APX78mL8Jnz59mt6+fUv6+vrUokUL/kbs4uJCIhE7Yk5TXLhwgfz8/OjRo0c0c+ZMmjJlCmlra/PvKzsPpYuRrPOQ4zi6fPkyn++1LCxk8tAucCk9NCj6iFVZydtfubm5tGjRIgoODiY7OzvatGkTNW7cmIiIUlJSaN26dbRy5Up68eIFeXl5UVBQEHXo0EHp4ysZnynKd9zMzIzatm3L+0EW5zv+8eNH2rx5M4WFhdGjR4+oadOmFBQURN27dyctLS3iOI5Wr15NU6ZMIVNTU1q3bh116NAhXxmamIs5OTkUHx/Pp+axsbGh8ePHK1ynKhCLxfTs2TPKzc0lBwcHmT6z9NgtWhGVwOsARSnr+kEVfBeCkujzk8asg7dJzEGuQ99FAiJxbg5Ve3uZzmycr7JFSWoC4ziO/3+iz1n8hUIhCQQCheoCQC9fvuQnsfTv4cOHBIC0tbWpTp06+USmNDF7YmIiubq6Uq1OfpRi21b+vhIKSEsooOCuToU+haWlpdHkyZNp7dq11LJlS9q4cWOBXGOKwHEc3bhxgzePR0VFUUZGBpmYmFCbNm34m7S9vf1XJyq+BjIyMmj69OkUGhpKbm5utHnz5iJPclJ4HgoFJABHr46E0ZrJg2nAgAFytVG6AErnmfT/876mLKocW9u3b6cff/yRRv+2g/55b6LyuXjr1i3y8/Ojq1ev0s8//0xz5swhA4PPZricnByKiIigkJAQunr1Kjk4OFBgYCANGjSI5ZCVEwB0//79fIE079+/JwMDA2rVqhX/8Fu/fv0SRfuTJ08oPDycNm7cSBkZGdS7d28KDAzMdzrTgwcPyN/fn6Kjo2nkyJG0aNGiIt2ClJmLnDiXMs/9Tld2L6eqVavmSwwu/YuPj6fc3FwSCARkb29PLi4uNHbsWGrWrBlflqJrnHTtlGYFka6X0rVTep1EIiEAJBKJSCQSkVgslitIDwD17NmTol9IqILncJKAVDoPvzW+G0FJ9NknYtr+mxT9MIVEQkGxA0P6fgs7c2pl+IIC+vlSaGgoBQYGqrxdACg5OZnu3r1Ld+7coXfv3pGenh45OjpSrVq1qHr16kpHqn78+JFu3ryZb8LfvHmTsrKyiOhzYvbU1FQCQOHh4WTn3IhWXnlP5+Tsq/nd65XoHxIZGUnDhg2jly9f0ty5cykwMFClO4k5OTl06dIlXmBeunSJxGIxValShb+Be3p6krW1tcrq/F45c+YMDRs2jJKSkmjOnDkUFBRU4lhVdB7O61aXZowfRREREXTlypUi04IUR05ODp/DzsDAgIyMjMjY2Jj09PR4cZmZmcn/cRzHL/TS/9fX1+f/1PGAcvv2bfLw8KBevXrR5s2b6fn7TIX6q6S5KBaLKTQ0lGbMmEGVK1emjRs3UqtWrfj3AdCFCxcoNDSU9u3bR8bGxjRs2DAaM2aMQm4r3wsvXrzgBeSpU6fo+fPnpKWlRY0bN+bvPY0aNSrWUiQFAEVFRdHy5cvpwIEDVKFCBRo5ciSNGjUq3+lqEomEQkNDafr06WRtbU0bNmygNm3alFi+InPRrbIhtdRPopkTRpNQKCRjY2P+nG49PT2qX79+vg2LevXqKf0gIhaL6cmTJ3Tnzh26f/8+ZWVlkampKdWqVYtq165NlSpVIoFAQNnZ2RQXF0dXrlyhDx8+UNWqVcnDw4McHBwUWmNCQ0Pp559/pv3791PDlu3VMg+/Jb4rQSnlwauPtONSIkXef00JbzPyvSegz0lH2zhY0sDGNnw01oQJEygsLIyioqLynRuqagDQzZs3KSIigvbu3Ut3796lcuXKUdeuXalnz57Uvn37fI7DyiAWi+n+/fsUFxdHv/32G8XGxlKFChXo/fv3RPT5HPLajduSXt129EHfmt7l5hcKRfWVLHz69ImmT59Oy5cvJw8PD9q0aZNCAkEWPn78SNHR0fwN/vr160T02Y9GeoNv3bp1keeuMwry8eNHmjJlCq1evZpatGhBGzZskNmEJCXvPEx8m5Ev9rSosfXp0ydq1KgRb85WdKHKzc2lP//8k0JCQujy5ctkZ2dHgYGBNHjwYLp79y4//548eUI6Ojr8YlWjRg3q1asX9ezZkxo2bKhyQZmenk7u7u6kpaVFly5d4ncNiRTrL1m4f/8++fv707lz52jUqFG0cOHCAqd4JSYm8gFPaWlpLO1QHj58+EBnzpzhXXDu3r1LRETOzs58+rMWLVrINVazs7Np9+7dFBoaSnFxcVSnTh0+cCTvmCD6fM61n58fXb58mQIDA2nu3LlkaCjfKSzFjS0ikCGXScJXdyjpzG56n3CHiD6vD6mpqdSgQQOaMGECubi4kL29vcrSdGVmZtLx48cpIiKCDh06RGlpaeTo6MjPv/r16/Nj79GjRxQeHk6bNm3ik5UHBgaSu7u7wvXHxMRQq1atKDAwkJYuXcq/rq55+E2A75xrN25D27I6thw6g1tJH5CelVvodTk5OWjatCmqVKmCN2/eaKx9t27dwuzZs1G3bl0QEYyMjNC3b19ERETg06dPKqljz549ICKsWLECHMchKSkJR44cwbx589CrVy/Y29tDIBBAoK0H3Uo1YVytHnz9x2HRb6GIjIzEu3fvFK77/PnzcHR0hI6ODubNm4ecnByVfKfieP36NXbv3o2AgADUqFEDRAShUAgPDw/88ssvOHnyJDIzM9Xejq+V48ePw8bGBoaGhlixYgUkEonSZaZn5eLn4N9QsU6jYuchANy5cwdGRkbo378/OI5Tuu7z58/D09Pz8xgXCEBEMDExwfDhw3HixAnk5OQgJycHJ06cwPDhw2Fubg4igq2tLSZMmIALFy6opA84jkO/fv1gZGSEu3fvFnttelYuLB0bIDA4pMT+kgWJRILw8HAYGhrCxsYGx48fL7ze9HSsWrUKDg4OICK4ublh+/btyM7OVqr+r4mMjAz8888/mDp1Ktzd3SEUCkFEqFGjBoYPH44//vgDr1+/Vqjs5ORkzJ49GxUrVgQRwdvbGydOnCh0nOfk5GDu3LnQ0dGBo6Mjzp8/r/B3evfuHSIjIxESEoIBQ/xgXLU29CrXgrZldQh19OHg4IDevXtj/vz5OHr0KF68eAGO4xAeHg4iwt69exWuOy/p6enYu3cv+vTpA0NDQxAR6tati9mzZ+PWrVv5+oHjOERGRsLHxwcCgQBmZmb49ddfkZSUpHQ73rx5gypVqqBZs2bFrknpWbnYfuQMdKwccPh8nNLz8GvnuxeUd+7cARHh3LlzJV777NkzmJub44cfflDJAiIvd+7cwdy5c+Hi4gIigoGBAXr27Indu3fj48ePCpV57949GBsbo2/fvsUuzmlpaTh//jyaNWsGc3NzuLu7Q09PD/Q5ege2trbw8fHBrFmzsH//fjx58kTmxT4zMxNTp06FUCiEq6srYmNjFfouivLkyRNs2LABffv2haWlJYgIurq6aNu2LebPn49Lly5BLBZrtE1lkffv38PPzw9EhHbt2uHJkycqLX/evHmwsLCQ6dpdu3aBiLB69WqF6hKLxYiKisK4ceNQuXJlEBHMzc3h6uoKY2NjCIVC9OjRA9HR0QXGcW5uLk6fPo1Ro0ahUqVKICJUqVIFgYGBiIqKUnisrFq1CkSE3bt3y3S9hYUF5s2bp1BdRfH48WN4enqCiODn54f3798Xep1EIsHRo0fRvn17EBGsrKwwd+5cjT5sa4rc3FxcvHgR8+bNQ9u2baGrqwsigqWlJfr164cNGzYoPRfi4uIwdOhQ6OjowMDAAKNGjSr2oSI2NhYuLi4QiUSYOnWqzA/AHMfhyZMn2L9/P2bNmgUfHx/Y2try93E9PT14eHjAwsICzZs3R0xMTLFrC8dx6N27N4yNjXH//n25vzfweW3ZtWsXevToAX19fRARXFxcMHfuXNy5c6fA9VlZWdiyZQu/Djo5OWH9+vXIyMhQqP4vkUgk+OGHH2Bubo5nz56VeP25c+dARIW29XuDCUo5BCXweXdGIBBgzpw5am5Z8Tx48AALFy6Em5sbfyPo1q0btm/fjg8fPshUxqdPn1CvXj04OjoiLS1Nps8MHz4cbm5uAD7faG/fvo0dO3Zg0qRJ8PLygoWFBX9zqlChAlq1aoXAwEBs3rwZsbGxxe5kXLlyBfXq1YOWlhZmzJiBrKwsmdqkSjiOw40bNxASEoLOnTvDyMgIRITy5cvDx8cHYWFhiI+PV8nO2NfEgQMHYGVlhXLlymHDhg1q+f7yCEoAGDVqFHR0dHD16lWZri9MCFauXBnjxo3LJwSlu3COjo4gIjRs2BDbtm0rdOwWJkwrVaqEUaNG4fTp0zKLyytXrkBHRwejR4+W+furQ1ACn+fA+vXrUa5cOVhbW+PgwYPFXn/r1i0EBARAT08Penp6GDZsGG7evKnydmkKjuNw+/ZthIWFwcfHB+XLlwcRwdjYGJ07d0ZISAhu3Lih9BwQi8U4cOAA2rRpAyJC1apVsXjx4mItPllZWZgxYwa0tLRQr149XLlypchrs7OzERsbi82bNyMwMBCtWrXivwsRwcLCAu3bt8fkyZOxc+dOxMfHIzf38w6bm5sbhg8fLtP3SEtLg4ODA+rXry+zqPvw4QO2bdsGHx8fXqC7ublh4cKFePDgQaGfSU5OxqxZs/iH/k6dOuGff/5R+b0oODgYAoEAJ06ckOl6Jij/gwlKOQUlAMycORNCoRCnTp1SY8tk58mTJ1i6dCkaN24MIoKOjg46d+6MLVu2FHtzGjp0KPT19eW6+ecVlIVRnMmciKCtrQ1nZ2cMHjwYISEhBUzm2dnZmDVrFrS0tODk5IRLly7J3DZ1kJOTg/PnzyM4OBitWrWCtrY2vyMzcOBAbN68GYmJiaXaRnXy5s0b9O/fn7+By/LErijyCsqsrCy4ubmhevXqRY7zvKZq6cOOjY0Nxo8fj5iYmGItDdJduB9++IEXinPmzCnSnCmRSBATE4Px48fDxsaGX7RHjBiBf/75p0jT2bt371CtWjW4u7vL9RClLkEp5dmzZ/D29gYRoX///iXuPr558wbz5s2DtbU1iAheXl44cuRIqVhz5CUxMRGbN2/GwIEDYWVlxd9HW7VqheDgYMTExKjMHSctLQ3Lly9HzZo1QURo2rQp9uzZw4u5orh06RKcnJygpaWF2bNn53vAyWuyHjx4MJydnfl7lUAgKNJkXRTyCEoAuHHjBvT19eHv71/kNW/fvsXmzZvRqVMn6OjogIjQuHFjLF26tNgd3tjYWAwePJjfvR09ejTu3bsnc9vk4eTJkxAIBJg1a5bMn2GC8j+YoFRAUIrFYrRr1w6WlpYq8ddQJc+ePcPy5cvRokULCAQCaGlpoUOHDtiwYUO+BWHTpk0gImzZskWu8ksSlEUhNZmvXLkSAQEBJZrMjx49CldXVwiFQkyaNEll5gxlSU9Px99//41JkyahQYMGvFB2cHDATz/9hIiICLx9+7a0m6k0HMdhz549sLCwgKmpKbZv3672XVl5BSXw2URboUIF+Pj48O3Lzs7G0aNH4efnB1NTU96/bfLkybh8+bJC3+P27dsYMWIE9PX1oaurC39/f9y4caPI6zmOw+XLlzF58mTeT9fMzAz+/v44duwYLwY4jkPXrl1hYmIit9lU3YIS+Ny+bdu2wcTEBBYWFtizZ0+J/ZednY0dO3bw1hMHBwesXLlSYbccdZCSkoK9e/di5MiRsLe354VXgwYNMHnyZBw/flxlPupSHj16hKCgIJQrVw5aWlro37+/TA/MGRkZmDhxIoRCIRo2bIijR4+WaLIePnw4Vq1aVaLJuijkFZQAsHnz5gJryps3b7B+/Xr88MMP0NLSgkAgQPPmzREaGlrsg7hYLMb+/fvRqlUr/iFwyZIlSvnrl0RSUhIsLS3Rrl07udxWmKD8DyYoFRCUAPDq1StYW1ujZcuWJT5ZlhYvXrzAihUr0Lp1awiFQohEIrRr1w7Tp0/nF0V5UVRQFoYsJvPq1atDJBKhYsWK2LRpU5lz/k9JSUFERESBhalhw4ZqW5jUzcuXL+Hr6wsiQo8ePZCcnKyRehURlABw8OBBEBGGDh2KQYMG8WY9e3t7TJs2DdeuXVOZGE5JScGCBQt487anpycOHTpU7C4cx3G4du0apk2bxo+RChUqYPDgwRgyZAiICIcOHZK7LZoQlFLyjglfX1+8fPmyxM9wHIfz58+jV69eEIlEqFChAiZOnIinT59qoMX5+fTpU4kPgikpKSqvl+M4nDlzBt26dYNAIICpqSmmTZuG58+fl/jZ7OxsbNy4ERUrVoRIJEL16tVRrlw5mUzWyqKIoAQAPz8/6OvrY/r06fD09IRIJIJQKETr1q2xYsWKEjdgUlNTERISgurVq4OI0KxZM+zdu1fta2xubi5atGgBa2trvHr1Sq7PMkH5H0xQKigoASA6OhoikQhTpkxRQ8tUS3JyMtasWYPWrVvzN6SWLVvKNMnzokpBWRiFmczzPoELhULUq1evSJN5aZPXdCb105OazubMmYOYmJgy+wDCcRy2bt0KExMTWFpaqixyU1bkFZQZGRnYt28f+vfvz5vQqlWrhpkzZ6rEx604cnJysGvXLnh4ePDiNTw8vMTdIKmP7syZM1GtWjV+fAwYMAD79u2Taydek4JSyt69e2FhYQETExNs3bpV5j5OSEjA5MmTUaFCBQiFQvTs2RPnzp1T229U2q4qXwaO1KlTB+vWrSvy4fJLk3XdunX56HHpuJbHZK0s8grKpKQkhIeHo3nz5nybW7dujTVr1sj0QPrw4UMEBgbC2NgYWlpaGDBgAC5fvqzMV5CLyZMnQyQSITo6Wu7PMkH5H0xQKiEoAWDx4sUK7zBoGo7j0KtXLxgaGmLevHno0KGDXGYIQP2Csijev3+PcePGQVtbG0ZGRnB0dFRZlLm6kMW5/+bNm6XeTiC/v9yAAQNKJVpXFkGZnp6OPXv2oHfv3nxakfr162PWrFlo2LChQjsMynLhwgX06dMHIpEI5cuXx4QJE0o0X0stHA0bNsTs2bNRv359EBEMDQ3Ru3dv7NmzB+np6cWWURqCEvhsxhwwYACf1kYev1p1pR36MpjO2Ni4VILpSkr7I0uUtaOjI4yNjaGtrY3AwECZgyxViSyCMjExESEhIWjWrFk+96p58+bByMgIffr0Kba/1Zn2Rx4OHDgAIsKSJUsU+jwTlP/BBKWSglIZHyhNExYWBiJCREQE/9q7d++wZcsWdO7cWSZH6dISlFIePnzI77L6+/vj4sWLKosyVzdFpR+pWLGiytKPyAvHcVi7dq3MEb3qpChBmZqaip07d8LX15dPK9KgQQPMnz8/n3O+oj5QqiIxMRFTpkyBiYlJsWmHxGIxPD09YWlpiRcvXvCv37t3D/Pnz0eDBg1ARNDX10ePHj2wa9euQrMwlJaglHLw4EFYW1ujXLlyWLdunVxiTRVph2RJ96Upa0BhaX9u3LghV5T1pUuX+LRcbdq0wcOHDzXS9sIoSlA+fvwYS5YsQaNGjYoNAN27dy+IPuc2/pLMzExs3rwZzs7Oakn7Iw+F+WDLCxOU/8EEpZKCEvgvStPNza1UUt3IwsWLF/kn3qL48OEDtm/fjm7duhWZyqG0BSXweTFas2YNjI2NUblyZRw+fJh/T9koc02SkZGBkydPFkiQXLNmTT5Bsjp3Ch89eoS2bdvy4ryonIOaIq+gfP/+PbZu3YquXbvyY9HDwwOLFy/Go0ePiixDkShNVZOeno7Vq1cXmXZIliwRjx49wuLFi3mTuq6uLnx8fLBt2zZ+x6q0BSXw+Xfy9/fn/UkfP34sdxmyph0q6kACd3d3/kACTYqSL9P+WFpaokuXLujbt6/cUdaHDx9G5cqVYWxsjDVr1pR6ZHxeQfngwQMsWLAADRs25MeiLCnqpBYlqelaU2l/ZCVvlghl7n1MUP4HE5QqEJQAcPXqVbnzyGmKlJQU2NjYoHHjxjLv0KWlpWH37t3o2bMnDAwMQPQ52aybmxvq1q2r5hbLRkJCAp/S5ccffyw2ulreKPPSMJm/f/8e+/fvx5gxY1CrVi2+bc7OzpgwYQKOHj2qkkhZiUSCsLAwGBgYwNbWVuZ8a+rm119/hbGxMby9vfnFuGnTpli2bJlcgRzSPHJFnfaiKSQSCY4dO5Yv7dDgwYNBRHLlsX369CmWLVuGpk2b8g9FnTp1grGxMX799Vc1fgPZkZ6eZGBggLCwMIUE0Zdph9q2bYvZs2fj559/5neziAi1a9fGmDFjsH//fo0/BElN635+fjAxMeEFlqJR1ikpKRg4cCCICB06dEBCQoIGv03R1K1bF25ubny/5z1EQ9acxdnZ2WjUqBGsrKzQt29fjaT9kQd589gWBROU/8EEpYoEJSD/SReaQCKRwNvbG6ampgrfrNLT0xEREYG+fftCS0sLREUfh6VpOI7Dli1bUKFCBVSsWBF//vmnzJ8tLMpceqxeWTCZP3/+HFu3bsXgwYNRpUoVEBG0tLTQvHlzzJ49G9HR0XLnxrt37x6aNWsGIsKYMWNKPZXL69evsW7dOrRv357foW3ZsiXCwsJkioQtDHlPutAEt2/f5oWDUCiEn59fsWmHiuL58+cICwtDy5Yt+bLat2+PdevWKXzcn6pIS0vDqFGjQERo3ry53KIhOzsbUVFRmD59Ou9jKR3zjRo1wrp16zTqX/dlYnAPDw/eLUgqJBs1aqRwlHVERAQsLS1RoUIFbNmypdTvozdv3sSsWbPg5OTE97v0mN+S/Hm/RJr2R2oa19PTw6JFi8pMAKX0pK01a9YoXRYTlP/BBKUKBaU8Z/Fqivnz54OIcPToUZWU5+fnBzs7OwwcOJBPYVGrVi1Mnz4dcXFxpXZTfPHiBXx8fEBE6NWrl8KpbsqqyZzjONy7dw8rV66Er68vvztiaGiIjh07YunSpYiNjS1yZyg3NxeLFy+Gnp4e7OzscPbsWbW3uShevnyJVatWoW3bthAKhRAKhWjbti26du0KMzMzldQhPYu3adOmGjkfviRycnLQtGlTWFlZYfr06XKlHSoKMzMzdO3atUA/rlq1Sqa0PurizJkzqFmzJvT09LB48eIiRZZEIkFsbCyWLl2KDh068EFWJiYm8PX1xcqVK7Fr1y6NpB0qLjG4dJ5J/Vr79OmDf//9V+F7XXJyMnr27Akigo+PTz4/Wk3CcRxiY2Px66+/8u4Z5cqVw8CBA2FnZwc/Pz+5yyws7c+0adNARFi4cKEavoX83LlzB4aGhhgwYIBK1ismKP+DCUoVCkoA+PjxI2rVqoW6deuWev7ByMhICIVClZrF8vpQZmVl4fDhwxgyZAgqVKgAIoKdnR2mTp2Kq1evalxcchyH3bt3w9zcHGZmZtixY4fK2lDWTOZisRhXr17FwoUL4eXlxQermJubo3fv3li7di0ePnzI7zxIfTQnTpxYKuMy786aQCCASCQqsLOmaB7KooiJiYGWlhYmTJigsjIVZfz48dDS0kJMTAwAxdMO5SWvD2XenV6RSASBQICWLVsiPDy8VA5f+PTpEyZMmMD7OEqzGTx48ABr1qxBr169eGuAvr4+vLy8sGjRIly9erXQgCpVpR2S9Sxrf39/DBo0iM8bWlLaH1nr3rFjB8zMzGBubo7du3eXyj3yypUrmDJlCn9ST4UKFTBkyBAcPnyYjwGQN21QSWl/pk2bBpFIVKoPssBna5uTkxNq166tMusME5T/wQSligUl8NnJ3MDAAIMHDy61HbuXL1+iYsWKaNOmjUojXosKysnOzsbff/+NYcOGwczMjM+dNnHiRFy8eFGj/fD69Wv06dMHRIQuXboobDotibJkMs/KykJkZCSmT5+Oxo0bQyQS8W0QCASoXLkyjhw5opa6iyIhIaGA75+3tzc2bdpUaBJpVQtKAFi2bBmICPv371dpufKwb98+EBFCQkIKfV+RtENA0UE5KSkp2LRpU6G+qJr20Tt8+DCsra0hFAr5CGeRSIQmTZpg+vTpiIyMlCuQUZ60Q4qcZf38+fNi0/4oyvPnz9GlSxcQEfr27atR9wSJRIILFy5gwoQJvHg2MzPDsGHD8Pfffxfad7IISnnS/uTm5qJ169awsrLS2EEJX8JxHAYNGgQDAwPcvn1bZeUyQfkfTFCqQVACwNatW0FE2LBhg0rLlQXp5K1UqZLKTV+yRHnn5ubi5MmTGDlyJB/RV7VqVQQFBeHcuXMai2Dct28fKlWqhPLly2Pjxo0aEbVlxWR+9uxZVKtWDQKBIF8qpbp16yIoKAiHDh1CamqqyustLDq5a9eu2Lp1a4kBFOoQlBzHwdfXF+XLly82OlxdPHz4EOXKlUOPHj1KHH+yph2SIkuUt6LR8oqSmpqKgwcPIjAwEHXr1s0n3gQCAapXr46oqCil6/ky7VClSpXg7++POXPmKHSWdWFpf1ThtsRxHDZs2IDy5cujUqVKGnuwkUgkiI6ORmBgIO9/bWlpiZEjR+LkyZMl+noWJygVTfvz8uVLVKpUCW3bti2VtF7r168HEWH79u0qLZcJyv9gglJNghIAnwojLi5O5WUXx7Rp0yAUCnHmzBmVly1v2iCxWIwzZ85gzJgxsLKy4nPOjRkzBmfOnFH7jeXt27d8ZK2Xl1epHPsGaM5knpmZyZuXnJ2dce3aNQCfb+Y7duyAn58fv0uhzE5RXr7Mn6inpwdfX1/s3LlTLtGqDkEJfE6HVbNmTbi6uiIzM1Pl5RdFZmYmXF1dYWdnJ1dy6pLSDkmRN21Q3nye0rEnzed5//59mcvJS1E747a2tvDz88POnTv5Halr167B2dkZIpEI06ZNU+i3KMxkLb2v5BWvPXv2LDHKWiwW46+//uLz2latWhWLFy9W2QPekydP0K5dOxARhgwZonZfa7FYjMjISIwePVrpe21hglIVaX+kbljTp0+X+TOqIDY2Frq6uhgxYoTKy2aC8j+YoFSjoFR0QVGGI0eOgIiwYMECtZSvTB5KiUSCc+fOISgoSKGnZmU4evQoqlSpAiMjI6xcubLU87wBqjeZX7hwAbVr14a2tjbmzJlTZDAKx3F4+PAh78smdVHQ19dH+/bti/VlkxIfH4/g4GD+hBcDAwP+hBdFfZPUJSgB9S4oRTF8+HClHigLSzs0Z84c3lyqTB7Kjx8/8icOSdOC1a9fH8HBwYiPjy/yc0X57pqZmaFXr175fHcLIycnB3PmzIG2tjZq166NCxcuFFmXvCbr8+fPY86cOXzaIS8vLxw5cqTAXE9NTUVoaCify7Jp06bYs2ePyu4/EokEK1asgKGhIapWrYpjx46ppNzCyM3NxT///IMRI0bwQq9KlSpKW4PyCsrY2FgMHjw4X9ofZXZvVR0oWhLSB8oGDRqo5YGSCcr/YIJSjYIS+GzyKl++vEwmL2VJSEiAqakpOnfurDbBpKrE5hKJBBcvXsTEiRP5M43z+vWoIzI3NTUVI0aM4FPTSJO1lyWKMplLF9HCTObPnz/H+PHjIRAI4O7ujlu3bslV55fRtlKBYWJigh49emDVqlW4e/curl+/jpkzZ6JOnTog+nyEZP/+/bFv3z6VBPqoU1AC6jN5FYaqXV5u376NESNGQF9fH7q6uvD394eJiYlKEpt/+vSJPxNdemRhnTp1MHPmTFy/fh137twpkF3AwMBApuwCRSENFBMIBBg/fjyeP39eZJS1LCbrvOTm5mL//v1wd3cHEcHBwQErV67EjRs3EBQUxAeO9O/fv1jxrAj3799HixYtQEQYOXKkWtxKsrOzcezYMfj7+xfqr66Ke/+OHTvw559/Ys+ePVi2bBnWr1+PK1euqESQqSKVnaxwHIfu3bur1eUlKSkJy5YtKzYP8vcCE5RqFpTAf075oaGhaqsjOzsbHh4esLW1VevAVsdJORzH4erVq5g6dSrs7Ox4MfNl5KGqOH36NGrUqAF9fX389ttvpeLPIy8lmcwFAgGcnJwwY8YMpaPMpfkAZ86cCRcXFz4/pFTQNm/eHFu2bFH50766BaW6nPK/RJ1BeSkpKViwYAGfdqhmzZoKpx0qDKl/XLNmzfKlzREKhXBxccHMmTMRFRWlcHBZXpP1jBkz4OTkxPsX542yljUxeEl1nT9/Hm3atOHr0NPTw+jRo1WeqkcsFmPp0qXQ09NDjRo1it15VYScnBycO3cOgwcPVmtGDY7jIBaLkZ2djezsbOTk5EAsFqtlHNvY2KBRo0Zqze2riaA8iUSC7OzsMmH1Km2YoNSAoAQKpg1RNWPHjs13zJW6UPfRixzHIS4uDtOnTy+QG+2vv/5S2dFq6enpCAoKgkAgQKNGjdQqMNRBWloaRo4cCSKCo6Mj/P39VRJlznEcLl++jMmTJ/MmQRMTE3h5eaF79+68iZtI9SeWqFtQAupJG5IXTaUNy8nJQbly5XjXEUXSDkkp6oSm+vXro3v37vDy8uJ3JmvUqIHJkyfj8uXLJYoMWU3Ww4YN4+f6yJEjZT6JpSQ4jsOdO3dQr1492Nvb44cffkCFChUwePBgfPr0SWUi6fbt22jUqBEEAgEmTpyoMtN5Tk5OgYfpR48eYenSpaWa81dVXLp0qcTjgJXh/PnzZSZt2PfCdy8onz59ipYtWyp0aoU8SBMbV6lSReXnM+/ZswdEhBUrVqi03MJYsmSJXPnJlIHjONy6dQuzZ8/mI0aNjIwUPr2hMM6fPw9HR0fo6Ohg3rx5ZSIJdklIj7kzNDREeHh4vidjRUzmKSkpiImJwfjx42FjY8Pnsxw+fDhOnDhRoE+KOlPZw8ODP1NZkd3L9evXo3Xr1kr3T0m8e/cOR44cwbVr11S6KGv6YIPWrVtj/fr1uH79OiZNmgRXV1c0a9YMS5cuLTZVVlFnyNeoUYM/Q/7LtDY5OTk4ceIExo8fjw0bNiA1NRUfP37EixcvkJCQgLdv3xZqsjY2Nsa4ceNw48YNpKenIycnB8+ePcOrV6/y9b1EIkF4eDgMDQ1hY2OjsmMzpbtr0rqkYk8Vu0k5OTmYO3cudHR04OjoiPPnzytdZkZGBp48eYLc3NyvwnKiLOHh4SAi7N27V6XlSg82aNas2VdxT/9W+O4FpSZ59uwZzM3N8cMPP6hse/zevXswNjZG3759v/on1pK4c+cO5s6dCxcXFz6IpEePHnKdL1sYmZmZmDp1KoRCIVxdXREbG6u6RquQ9+/fw8/PD0SEdu3ayZSrUMqXJnM3N7d8x8hJU/y4ubkhODgYDx48kHk8PXnyBBs2bEDfvn35wABdXV14enpi/vz5uHz5cpkzB0lFhirnzOPHj1GtWrUydfRqTk4OJBIJLl++jHnz5qFt27Z8+iBLS0v069cPGzZskHksfdlnEomEN5GuX78erq6ucHd3x7Rp0xAXFye3ufTx48do27YtiAh+fn4aP6tbVmJjY+Hi4gKRSISpU6cq5f6RlpaG6Oho3p/zexJAHMehd+/eMDY2VjjTwJeUxaNXvxeYoNQwx48fh0AgwJw5c5Qu69OnT6hXrx4cHR1VZib6Wnjw4AEWLlwINzc33jeqW7du2L59u8IR9VeuXEG9evWgpaWFGTNmqNx3UxkOHDgAa2trlCtXDhs2bFBICOXm5uL06dMYNWoUKlWqxIuKH374Af369UO7du1UYjK/ceMGQkJC0LlzZxgbG+PAgQPfxW4LgDL5UCcWi3HgwAEYGxujc+fOCAkJwY0bN+Q2WUdERBRrzpUKoZSUFHAcp/BDBMdxWLduHYyNjWFtbY2DBw8WeZ2mycrKwowZM6ClpYV69erhypUrCpUjFeY5OTl84I46s1xI6yyLpKWlwcHBAfXr11eJS1NwcDAEAgFOnDihgtYx5IEJylJg5syZ8PDwUDqo4fLly7CwsMDNmzdV1LKvkydPnmDp0qVo3LgxiAg6Ojro3LkztmzZInfut+zsbMyaNQtaWlpwcnLCpUuX1NRq2Xjz5g369+/P532T94lbaqocPnw4n+DcxsYG48ePR0xMTIFFXxGTeXF9rO5FsqxRVhdtAOjQoUO+tEN5Ke4sa4FAgMaNG8v8W6qqDxITE+Ht7Q0iQv/+/XlXIU0dHSqRSPgdXuCzz5+TkxO0tLQwe/ZslQWTqHvMXLt2DYMHD9ZoDlZ5uXHjBmxsbJROvZOTk4N27dph1qxZqmkYQy4EAEAMjcJxHHEcR0REWlpaCpcjFospMzOTjI2NVdW0r55nz57Rvn37KCIigs6fP08ikYjatWtHPXr0oG7dupG5ublM5dy4cYOGDh1KcXFxNGHCBJo/f75Sv5UifPr0iapXr04SiYTCwsKof//+JBAISvxcTk4OnTp1iiIiIuivv/6id+/eUY0aNahnz57Us2dPcnNzk6mcvHz8+JFu3rxJcXFx/N/NmzcpKyuLiIhsbW3JxcUl35+tra3c9TDUAwD6+++/qUePHiSRSKhly5ZkZ2dHL1++pLi4OEpISCAiIj09Papfv36+37FevXpkZGRUau3evn07BQYGkkAgIC8vL1q5ciVVqFCBRCKR2usXi8V04sQJCgkJoVOnTlGDBg1o06ZNVL9+fbXXrQwSiYQOHTpEoaGhdPbsWbKxsaFHjx5p/B4mD5mZmaSlpUXa2toKlyGRSEgoFBIAEgqFKmwdQyZKVc5+x5TlnYxvhaSkJKxYsQKtW7eGUCiESCSCp6cnVq9eLdN5srm5uViwYAHatWungdYWzsSJE2Vqa2ZmJg4ePIhBgwbxkbT29vaYNm2ayoNPpMiSmP3YsWPfjbm7LCMWi3Hs2DE+z6T0z9TUFL6+vti+fTvi4+M1vqMskUiK3TnjOA5nzpxBhw4dQETYunWrXG2Ujvuixr+s86Jbt27Q09PD+PHjS+20LVlITU1FSEgIqlevDiJCs2bNsHfv3u/OUsAoHZigZHwXJCcnY82aNWjXrh1EIhGEQiFatWqF8PBwJCUlFfvZ7OzsUhFFJfmgZWRkFJmQWhYfOXXwpck8KiqKLWZlgNzcXERFRfGJwRMSErBz507+zHVl0g4pg1gsxuzZs/kE+VIfuqysLGzZsoUPwKtTp45cJ85I5448c6Coa6VBR7NmzUKFChUgFArRs2dPnDt3rkTBqiyylv/w4UMEBgbySdsHDBig9hRyDMaXMEHJ+O548+YNNmzYgA4dOkBLSwsCgQDNmzdHaGgoEhMT1Vq3ssI0PT2dPzLP0NAw35F5X1suTVUQHx+v8sW8tIR4af1+Fy5cQJ8+fSASiVC+fHlMmDBBrgwCysBxHLKysvjIbgMDAzg5OaFcuXIgInh7e+PEiRNy/SYSiYR/iJkyZQpmzpwpc+R0SfWkp6dj1apVcHBw4FMtlfYJKWPGjIFAIICZmRl+/fXXEh+QSyIpKQkzZ85E//79MWHCBHakYAmw/voPJijLEHmdzaU3wO8phURp8O7dO2zevBmdO3fm0+g0btwYv/32m8rOX58zZw7GjBmj8Oc/fvyInTt3wtfXlz87uUGDBpg/fz7u3bunkjZ+rZibm6NixYpyp78pC3yZbsnc3LxU25OYmIgpU6bAxMQE+vr62Lt3r8Z25jmOw5EjR2BqaprvVBtfX1/s3LlTpuwC69evR2RkJP/auXPn0KJFC4SHh6ssIOXly5dYsmQJv7M7cOBAmT4n7cfr16/j4cOHKmkL8Hl9+OOPP7B+/XqFI6T19fX5QK3bt2+jfPnysLOzQ69evVCrVi0YGBjg+vXrKmuzPJTFNbEs91dpwwRlGWLdunUFblDSdEDr1q1T6xFVDODDhw/Yvn07fH19ERkZqZKdqoSEBAgEAggEAvz1118A5It8lkgkmDdvHogIHh4eWLx4sdrOpP0aWblyJYKCgvIl6K5ZsyafoDslJUWmcqQL/h9//IGLFy+qbZdSLBZjxIgR+RLCu7u74+eff8bKlSvVUqe8pKen48WLF3KJSamJOSYmBs2aNVMosXtubi5SUlLw/v17PHr0CIsXL4aHhwc8PT1L/CzHcdi4cSO0tbUREBAAsViMfv36ITAwEI8fP+avyXu9vCJTIpHgxYsXsLCwQLdu3bBz505IJJISx4pYLOb7slu3bhg2bJhKdzWVHasCgQCvXr0CAPj4+KBLly75EsD37dsXnTt3VrqdilAW18Sy3F+lDROUeYiLi4NQKCy1+p88eQILCwvMmzcPwOcnsUaNGqFjx44wNDTE9u3bS61thVHa/fU1cOLECbi7u2Ps2LGoUqUKv4jJulhzHId3796V6UAARTly5Aj8/f0xadKkAmaid+/eoU2bNiWWIQ0CsrW1hbe3N/r06QNvb2/+TPigoKBiPy/NlyhdlFu0aIEZM2bkExtSsdS1a1fs3btX6QXc29s7X1ttbW3504mKQhV9pQ7yiqU//vgDPj4+8PLyyhdIpmx/5ebmypzTMjY2Fl5eXihfvjwaNmzIuxFIUwBJiYiIgLm5uUwBb3n5spziSElJybdrGBcXh1atWuHPP//Md520/2bNmlUqFoe8Aqlq1aqIiorK9/61a9dgZWWl8XYBZXNNLMv9VdowQZmHuLg4CASCUm1DREQEzMzMkJubizt37qBy5coQiURYtWpVmcsjVhb6q6xz6dIldO/eHTExMahVqxYGDRpU2k0qE+zYsQMikQidOnVC8+bNoaenl29xSE5Olulh5e7du0VGmZcrVy5f4ERJPHnyBC1btsT+/fsLvJeYmAiBQIBz587xr0lFjrwJ8Fu0aJHvLOvJkydj586dRYoJVfWVKklPTy9wPxo0aBAEAgFq1qyZ7+jEI0eOYMCAAfjnn3/U2iapMLt06RKqV68OQ0ND9OrVK9817969g4WFBSpUqIBffvkl3+dUzdatW2Fubo5+/fohOTkZ//vf/xAQEMCbvKW7axkZGbhz5w4EAgFOnjwJjuM0GgQoFAp5E66trW0Bc+3jx4+hp6ensfZ8SVlbE8t6f5UmZTcplRrw9fUt9v3U1NRSzZsnFoupR48e1KhRI/rtt99o5cqV1KRJE3rx4gXt3LmTfvrpJ422p6z319fAvXv3KCsri5o0aUITJkygiRMn0t9//01JSUnk5uZGzs7Opd3EUmHJkiW0bNkyGjduHBER7dmzh/z8/CgrK4v8/f1lLsfR0ZEcHR2pf//+RPQ5b6E0t2JcXBzVrVu3yM8+f/6cNm7cSPXq1SNfX1968OABmZmZ8TkGc3JySEdHh+Lj46lu3bqkp6dH69evp5ycHGrTpg0JhUJ6+PAhLV++nKKiokgkElGPHj3Iz8+PrKysiqx37ty5ZG9vT5UqVZJp/qiqr1RJTEwMDRw4kLy8vGjSpEnk7OxMVatWJWdnZ6pbty516NCBvL296fDhw9SsWTM6fvw4+fj4UMWKFWnSpEkqv5dxHMfnpVy6dCl16dKFOnfuTCEhIWRiYkLr16+nnj17komJCZmYmNCzZ8/o+vXr/G/McZzK8xb++OOPZGtrSxs2bCB7e3sSCoU0ePBgqlmzJhER6ejoEBHRsmXLaMaMGVS1alWqVasWCQQCEolEJBaLaePGjdS7d28yMTFRadvyAoAcHBxIIBBQeno63bhxI1+ezYcPH1KlSpXUVn9xlLU1kahs91epU8qCVqNoaWmhY8eOGDJkSKF/Xbt2LTUTrnQXRSwWIyAgADY2Npg4cSLu3LmDT58+QUdHB6tWrQIAmfx2VEFZ7q+yxM2bN7F+/Xr+33mP/Dp+/Dj69+8P4PPv1r59ewgEAjg5OeHly5dl7oxrTWFoaMj7tkk5ffo0jIyM+Dyh6h5bz549w8iRI1G1alWUL18e5ubmcHZ25n1d89KvXz84Ojqia9euqFixIhYtWoTU1FT4+vqievXqOHz4MMLDw9GiRQsMHTpUpe0sC31VGFFRUfD19YWjoyOuXLmCmjVrYubMmQA+38cePHiQ7/pPnz5h7dq1sLW1hbm5uUqOn/2SefPmoUOHDjh9+jT/2uLFi3mT6R9//AGhUIjt27ejTZs2sLa2RkJCAnJycpCSkoLLly+rJWp7+vTpsLe3h4WFBRwcHLBkyRL+vZSUFOjo6KBWrVoQCATo378/3r9/j5cvX6Jz584QCATo2rUrYmNjVd4uANiyZUu+vwsXLuR7Pzg4GD///LNa6i6OktZELS0thIeH57tWE5TV/ioLfFeCsl69etiwYUOR78fGxpaqQHr79i06deqEBg0aYPXq1fnSPyQkJAD47ENy4MABTJ8+Xe3tKev9VVaYOHEibGxssG7dOtSuXRsmJib8cYSrV6/G8OHDAQBDhgyBtrY2LC0tedHxvSa4t7KyKnAjBoAzZ87AyMgIv/76q8bGVm5uLh48eIA6deqgfv36sLa2hqmpKWrXrs2boR0cHDB37lz+M2KxGPHx8ahTpw7WrVvHv753795iz59WhLLUV0WxZMkS1KlTp0izdt4HpwULFsDIyAj+/v4AVDcHcnJyEBgYiMWLF/P5NPOW/ebNG1SsWBFjx47lXzt16hQAYNOmTbC3t4ezszOsrKzw22+/Kd2evIKoffv2WLZsGZ4/f44NGzbAysqKv4fPmTMHVapUQVZWFuLj47Fw4cJ8wSa3bt3CwIEDYWBgADc3N5w8eVLptn0tFLcmSv0YgZJz9jI0w3clKIcMGYJRo0YV+X58fDyqVaumwRbl5+rVq3B2dsaWLVvyOXNzHMffnDIzM/Hnn3/CyckJU6ZMUWt7ynp/lTZ5FytbW1sIBAL8+OOP+a4JDQ2Fu7s7LCws0LBhQ5w9exYbNmyAoaEhjhw5oukmlxl8fHz43awviYyMhKGhoUZEkvQ3vH//Plq0aIF//vkHubm5uHLlCn777Te8ffsWiYmJEIlE+VLSAJ99JwcOHJjv3OAtW7bA1dUVe/fuzVe+MpSVvioOd3d3jBgxgvct+zKiGvjcXxs2bIBAIMCyZcvw/v37AteqgtTU1HzlSv87aNAg2NnZFQjEefnyJVq2bIn+/fvj7t272LdvH2rWrInx48cjJydH4fZJRc7OnTvRvn37fP63YrEYHz9+RE5ODqpUqVLoBoFEIsknlJKSkiAQCGBra4ubN28q1KbiaNOmDf+b5CU1NbXUgr6KWhOBz/1x4sQJ+Pn5oVevXpg7dy7/gKAJymJ/lTbflaDMysrKl9eqrHHhwgWYmpri/v37AIp2FheLxbh69SqMjIxw6NAhtbWnrPdXWeH06dNwdXWFubl5gZx3x48fR/ny5bFo0SJ+1yQxMRHdunUrUiR8D5w5cwbz588v8v3Tp09jyJAham+HNN3H5s2b0b1790KTi2/fvh0mJia8WJLy4sULBAUFQVdXFxYWFvDy8kLTpk3x66+/FrrQKEpZ6asvkQqtqKgo2NraYvfu3cVeP3/+fFSvXh0//fSTJpoH4D9Rd+7cOQgEAvz9998A8ovYjIwMNGnSBAcOHOBf27x5M5ydnXlxqgyjRo3CqFGj8oltaf07d+6EgYFBkbkppWtAXFwcevfuDRsbG7WdgJM3ejkvr169gpaWllrqLIkv10Qply9fxuDBg+Hi4gJ3d3eEhoaiR48esLW1LTSoTh2Uxf4qbb4rQfk10K9fP1StWjXfa9Kbz/79+3lTKgD873//Q7du3Vh+yjLC5MmTUa9evQJHxD1//rzAtapKms4oGll2lqTX/Pjjjxg6dGg+0ShdzAcPHowOHToA+E+AXr58GR06dEDr1q1x/vx57NmzB61bty5WLEkkkm9yrl65cgUuLi5FmvnFYjHWr18PgUCARYsW8T6KmjRTTpo0CY0aNUJ2dna+emNiYvDrr7+iQ4cO6NSpE//6ihUr4ODggH///Vcl9X/5MCJtQ+PGjTF48OBiP/vp0yc0atQIDRs25AWxKrl+/TquX78OgUCAyMhI/t/Xr1/HtWvXMH/+fNja2qq8Xlnp168fbG1t+bl38eJFtGrVCgKBAEZGRpg1axafm3f58uUoV66c3Omg5KGs91dp8l0KSqFQWOiTRUpKSqmbjgDg6NGj4DgOly5dyvd6QEAAPDw8+H8PGTJEIwlUy3p/lRZfpve4e/cuXFxc0L9//0KTj+fdmWB8RlVj6927d4iMjERISAgGDx4sd3qmV69e4e7du4Waaps2bVrAlWHq1Klo06ZNvt/58OHDBVLm5C3r5s2b0NbWhrOzMwYPHoyQkBBERkbme0gsjrI6D9PS0tCvXz+UK1cOgwYNKmAmXrx4Mezt7TFy5MhSa+OePXtgbm6OPXv28K+FhYWhfv36aN++PcLCwuDm5gYjIyP06dMHjo6O6Nevn1rblJaWBisrKz7YMi/S+8qtW7cwYMAAVKxYUa07k0KhEEKhkD+EIe+fgYEBNm7cqJa6ZSXv7nHnzp2hr6+PTZs2YceOHZg+fTosLS150T506FCEhYWprS1fQ3+VFt+loCxqqzopKanM5I/6888/MXny5HyLzcuXL2FpaYnOnTujW7duaNy4MaZOnap2ofI19Jc6kLVfo6KiYGJigtDQUBw8eBBVq1bFb7/9BrFYjEePHuWLAJe13u8FZcfWjz/+yCcGp/8/rs/FxYUPhFIFv//+OypXrozu3bvj6NGjAD5bBxwdHfPljkxLS0OVKlX43/vL33Hz5s1o3LgxWrduDWdnZ+jp6fHttrW1LSBav6Ssz8Pz589j6tSp/L/FYjG2bt0KHR0dzJkzhz+1qLQCKFavXg1zc3Ps378fHz9+xA8//IBRo0YhPT0dwOe8kL169cKoUaNw69YtvHnzpkB7VTk3MzIyMG7cOFSuXBlbt24t0C/Z2dlo2rQpGjRooFZ/66dPn+LJkycQCAS4cuUKnj59yv/Je2KSutmxYwf09fUL5H7s0KEDH8l/6dIlPohVHXxN/aVpvqs8lGFhYUREJBAIaMOGDWRkZMS/J5FIKCoqimrVqlVazcuHtbU1bdu2jbp06ULNmzcnIqJKlSpRixYtqGLFimRmZka1a9emiRMnqi0X5NfUX6oCAF29epUiIiIoOzubQkNDi71+/fr1NHLkSJo2bRoNGzaMDA0N6cyZM7R27Vo6ePAgnT9/nvr27UvDhg2TuQ1F/Z7Xr18nBwcH0tfXl+crlUlUNbaysrLIx8eHRCIRvXr1imJjYykuLo5evHhBa9asUcncGDRoENnZ2dHOnTvp5MmT1LFjR+rduzft2bOHdu/ezeeCXLJkCaWlpVH79u3575aXjIwMyszMpIsXLxIRUe3atcnV1ZUqVqxIYrGYXr58WWj9pTEPART6HYqjadOm1LRpU/7fW7ZsobFjx9KgQYNo+vTp/OtF5XsEkK++zMxMOn78OBkYGJCnpyefZ1JRRo4cSQMHDiSRSET6+vqUnZ1NaWlpZGhoSESf80LWqVOHLly4QE5OTnwf5G2vQCCgdevWkaurK7m5uSk1vvT19Wn58uVkb29PISEhVLlyZWrbti0Rfc5lOHv2bLp37x4dP36cGjZsqMQ3Lx5bW1si+pzLU8rz58/J2tpa5bk5lSU7O5ucnZ2pZs2alJubSyKRiCQSCb1//550dXWJiMjd3V2t+ZG/pv7SOKWrZzVLtWrVUK1aNQgEAlStWpX/d7Vq1eDg4ID27dvj4sWLpd1MnvHjx6N27dpISkpCbm4uPn78iObNm+P333/Pd526nvi/tv5SFIlEgpiYGIwfPx42Njb8MXjjxo0rsW8vX76MGzdu8OUAn3cW9uzZg0mTJindP9Jd0t9++w0CgQCGhobo06cP9u7dy++sfI2oamx5eXnxZ3jXqFEDAQEB2L17dwGfNVXDcRz27t2L+vXrw9DQEPXq1YOrqyuWLl1a4mdfv36N3bt3IyAgIN+Z3u3bty/0ek3Ow+TkZMyePRt9+vRBamqq0taPmJgYfqevuJ0biUSCzMxMjBw5El26dEHnzp1haGgIIoK7uzvfFlUgnadz585FixYt+ICYtLQ0TJgwAU5OToXWxXEczp49y5/GVLVqVRw7dkzlO1IfP36EnZ0d3Nzc+ACTor67RCLB+/fvVe6ba2xsXKjbTmmzadMm1KxZM9/3PXbsGPT09LBt27ZSa1dZ7S9N810JSimtW7fmTcnR0dFl7kjDvHTs2BFt27aFt7c3vLy8oK2tjStXrvDva8I8+jX1l6yIxWJERUXxJiciQsWKFTFq1CicPn2adwCXF3Wa8+7cuYO5c+fCxcUFRAR9fX306NEDu3fvRlpamtrqVSfKjq2AgABs2LABT548UUPrZCMlJQWnT58ukMhbVp48eYINGzYgICCg2OvUOQ9jY2MxZMgQ6OjowMDAAKNGjSoQWasuOI7D/fv30b9/f2hpafFuAE5OTti+fXuJ97hPnz4pNF+zsrLQu3dvmJmZ4aeffkKTJk1Qrlw53s+yqLn88eNHTJ48GWZmZrCzs1P5nE9PT0dgYKDMPpODBg2ClZUV5s6dy4t3ZTEyMiqzAqlZs2bo0KEDpkyZgp9++gkCgQCBgYGl2qay3F+a5LsUlHkp608Wnz59wsaNGzFgwAD4+PioJf+YPJT1/iqO3NxcnD59GqNGjUKlSpVARKhcuTLGjRuHqKioMuf7UtxC+uDBAyxcuBBubm6872C3bt2wffv2MhNBnp2djbdv38q84H7NY0vTyNtXEokEb9++zbezIxaL8ddff6F169b8jtvixYtlDhJSBRKJBEePHuV3IhcuXIjr169j9erVcHR0BBGhYcOG2LZtG8RicaFz4vjx40qdbnPw4EH4+/tjypQp2LFjR5HXvX37FrNmzYKlpSWICJ06dcLff/+NlJSUYu8d6n7ov337NgICAqCnpwc9PT0MGzZM6XWiLAuktLQ0TJ48GZ06dUKTJk2wa9culaR3Uoay3F+aRAD8v6PId4qxsTFdv36datSoUdpNkRl1nDsrK19bf+Xm5tKZM2coIiKC9u/fT2/evCEbGxvq2bMn9ezZkxo1alRsX759+5YqVKigtP+WvIjFYnrx4gW9evWK3N3di7326dOn9Oeff1JERARdvHiRdHR0yMvLi3r27Eldu3YlU1NTtbf3/fv3dP36df4M7bi4OIqPj6dNmzZR3759SUurZHftr21slSby9pVYLKbdu3eTn58f1apVi/T09Ojx48f09u1b8vDwoIkTJ1L37t1l+p1UzZ49e8jDw4OqVauW73WO4+jEiRMUGhpKx48fJ1tbW7p8+TKZmZkVOR/xhR+mouQtRywW08GDB6lv376kra1NQ4cOpbFjx5Kjo6PS9aiSlJQUWr9+Pa1YsYJevHhBXl5eFBQURB06dChxvdi6dWu+f48YMYLmzJlDlpaW/GuDBg1SS7u/Rlh/FQ4TlKW0iCkqCvPe6EpDWH4Ni35OTg6dOnWKIiIi6K+//qJ3795RjRo1eBEpizM9AIqIiKDRo0fTzp07qW3bthrtawDk5+dHW7dupQkTJtD//vc/mYJxnj17Rvv27aOIiAg6f/48iUQi8vT0pJ49e1K3bt3I3Nxc6XYlJCTkE45xcXGUkJBARER6enpUv359cnFxIRcXF/L19SVLS0uZFvmvYWyVFeTtKwD0+PFjCggIoHPnzuULaCD6HGgg/c2kf7a2tmoNbpBV/GVmZtLo0aNpy5Yt1KlTJzp06FCR16r6nshxHL17945q1apFWVlZFB4eTkOHDlVZ+eogNzeXIiIiKCQkhK5cuUIODg4UGBhIP/30U5H93aZNm3z/jo6OJjc3N/6eIxAI6PTp02pvuzxIx8+X40gT6+LX2F8aoTS2RcsSO3bs0Hhww82bN/mj2RSF4zhkZWVh/vz5Cvv7KUJp9JcsZGZm4uDBgxg0aBDKly8PIoK9vT2mTZuGa9euyWV2evnyJXx9fUFE6NGjR6mZkHNzc7FgwQLo6urC3t4e0dHRcn0+KSkJK1asQOvWrSEUCiESieDp6YnVq1fLlPg3OzsbsbGx2Lx5MwIDA9GqVSu+b4kIFhYWaN++PSZPnoydO3ciPj5eqbFYVsdWWUTevuI4DkOGDIGpqSmmTZuG58+fIzc3F7dv38aOHTswadIkeHl58QEnRITy5cujVatWCAwMVEtCbVmIjo6Gvb09dHV1sXDhQiQnJ+PmzZsaveedP38ez549Q/fu3fl7wsuXLzVWv6JwHIeYmBj07t0bIpEIWVlZMn9W0ybc3NxcrFy5ski3BlnhOA6nTp0q9MQrdcJM3p/57gWlpklNTYW9vT2cnZ2Vjsz7999/IRKJ1H6md1klIyMD+/btQ//+/WFsbAwiQp06dTBz5kzcuHFD7hsTx3HYunUrTExMYGlpqbToVxXx8fFo0qQJBAIBxo4dyx/hKA/JyclYs2YN2rVrB5FIBKFQiFatWiE8PBxJSUkFEoM7OztDW1sbRASBQAAHBwf07t0b8+fPx9GjR/HixYti+zcnJwfnz5/H4sWLkZmZqVEBwMhPbm4uPn36hP79+5cYcMZxHJKSknDkyBHMmzcPvXr1gr29PYgIN27cKPF3lPrLKhuo8vHjR4wdOxYCgQBNmjTBnTt3CrRT3b6JX5bPcRz27NkDCwsLmJqaYtu2bUq1QSKRFDhvXF0kJCTINQc1LZAmT54MkUjEZ8xQlJycHLi4uMDR0VGjgYpMUH6GCUoNwnEcevXqBWNjY5VFUC5evBhEpNYzvcsS6enp2LNnD3r37s2nFalfvz6Cg4OVeip99uwZvL29QUQYMGCAyqIlVYVYLEZISAj09fVRrVo1nDx5UqFyOI7Dv//+i9GjR8POzg4CgYDfkSIi6OrqwsPDA8OHD8eqVasQExMjk4DlOA43btxASEgIOnfuzAv88uXL45dffuFPTylu4ZRIJBoLjHr16hVOnDihsgjd0khGLxaLC7Sf4zi+H6V9np2djalTp6JcuXIgIhgbG6Nz584ICQnBzZs3ZWp7Wloabt68mU8E5SU3Nxe5ubk4ePAgNm7ciNevXyvcJydPnkS1atWgr6+P0NDQMhcs9+bNG/Tv3x9EBG9vbzx79kzhspKTk3Hw4EHEx8cD+CyIygKaFEgHDhwAEcmUcksW7t+/D2NjY/Tu3Vtj85IJys9894IyPT0d//zzD96/f6/2usLCwkBEiIiIUFmZHMeha9euMDEx0UjqlPj4+AJHQqqb1NRU7Ny5E76+vtDX1wcRoUGDBpg/f36+k0oUgeM4rFu3DuXKlYO1tXWR5xGXFR4+fMhH5QYEBBRrjpfFZN2mTRt4e3vD1dWV35Fs3Lgxli5dWuJ4kqa76devHx/5qquri7Zt22LevHm4ePGiXLsi8fHx+Ouvv2S+XlHEYjE8PT1haWlZ6MkzilLYsY3q5K+//uKFyLt373Dp0iXs3bsXERER+PfffwuMjdzcXFy8eBHz5s1D27Ztoaury6fL6tevn0zpl16/fg2JRML/AZ/F5u7du9GzZ898JvPq1atj7dq1/E5RSQ8UHz58QEBAAIgIbdq04fNDKkthO42q4MCBA7CyskK5cuWwbt06pctNSEhAfHw8JBJJqe/oz58/XyNr4uPHj1GhQgV069ZNpXNm7969ICKEh4errMzi0FR/lXW+e0F5584dEBHOnTun1nouXrwIbW1tteTLevfuHapVqwY3Nze5/GQUYfjw4XBzc1NrHQDw/v17bN26FV27duUXPg8PDyxevFhlT4KPHz+Gp6cniAj+/v5fzQ1BIpFgzZo1MDY2RuXKlXH48GGVmKw/fPiA7du3o1u3bnyfu7m5YcGCBXjw4AFev36NP/74o0BCbnd3d0ydOhUnT55ERkaGwt9r3rx5sLCwULZ7SmTmzJkQCoU4deqUysu+ePEi6tati0WLFqm87C+xsLDAgAEDFE77k5GRgX/++QdTp06Fu7s7nyC+Zs2aGD58OP744w+8efMGDx48wIIFC9CwYUMQEapUqYK1a9fi0qVL+PTpU74yCzOZ16pVC23atEFAQACCgoLQvn37AmeZHz58GJUrV4axsTHWrFmjkp1j6c7mkSNH8McffyAxMRFr167F3bt3VbYz/f79e/j7+4OI4OnpiRcvXqis3KysLHAcx38P6X+VmWNliaysLLi5uaFGjRpqufeOGzcO2traGt8A+Z5hglIDgjIlJQU2NjZo3Lixyk80kHL16lXo6Ohg9OjRailfijoF5du3b7Fp0yZ4e3vzYqhp06ZYtmwZnj59qrJ6JBIJwsLCYGBgAFtbW5w4cUJlZasbjuPw5MkT7N+/H0FBQfzOoPRPT09PIZP1l6SlpWHLli1o1qxZvmTT9P8n0owZMwb79+9X6UKgCUF5/PhxCAQCzJkzR211BAcHQyAQ4Pjx42opPzU1FaGhobwAbNq0Kfbs2aP0rta7d++wf/9+jB49mn9gkP5paWmhWbNm+P333xUeT+fPn8fKlSsREBAAd3f3fGeZExEsLS0RFBSE/fv348mTJ0rvWHEch6tXr6JJkyZ8Hdra2ggICFC5S8vx48dhY2MDAwMD7Nq1S6W7bZ8+fUJycjJiYmLQtWtXaGtrw9vbG5s2bVIq/2ZpM2rUKOjq6uLff/9VS/nZ2dlo1KgRbG1tv+p++ppgglLNglIikcDb2xumpqZqPbAeAFatWgUiwu7du9VWh6oF5evXr7Fu3Tq0b98eWlpaEAgEaNmyJcLCwvD8+XOV1SPl3r17aN68OYgIo0ePLtMnzMhisvby8oK3tzcMDAxgZmbGn/KhaH1RUVGYNWsWmjdvzgtJa2trtG7dGo0aNYKBgQF/ismsWbNk9sGTBXULymfPnsHc3BwdOnRQ64lGEokEP/zwA8zNzZXyr/uSR48eISgoCMbGxtDS0oKuri5++uknlZTNcRxu3ryJWbNmwcnJCUQEAwMDNGrUCK1bt4a1tTUvLJs3b45Zs2YhOjpaqQfkP/74A2ZmZjAwMEDHjh3Rrl27IqPMN2/ejNjYWJnrk0gkOHToEFq1agUigpWVFRo3bgw9PT3o6urC399faXeZL0lLS8OoUaNARGjevLnKywc+j+GwsDC0bNkSAoEAWlpaaN++PdatW6f240ZVya5du0BEWLNmjVrrSUhIgKmpKTp16qTWOc/4DBOUahaU8+fPBxHh6NGjaik/LxzHoV+/fjAyMsLdu3fVUocqBOXLly+xatUqtG3bFkKhEEKhEG3btsWqVavUlo4jNzcXixcvhp6eHuzs7HD27Fm11KMoypqsX7x4AR8fHxARevXqJZNvoEQiQWxsLJYuXYqOHTvyQU4mJibw9fXFypUrcffu3Xz1ZGRk4K+//sLAgQP5II9atWph+vTpiIuLU0pcqlNQ5uTkoGnTpqhSpYpGAq7evHmDKlWqoGnTpkoFWnAchzNnzqBbt24QCAT50v5YWFhg3rx5SpUdGxuLX3/9lT+Vply5cvjxxx/x119/5TOtchyHu3fvYuXKlfD19YWJiQmICIaGhujYsSOWLl2K2NhYmRbt5ORk9OzZE0QEHx+ffGbi4qLMpTuMzs7OBUzmUtLT07F8+XJUr14dRIRmzZph7969/O5tSkoKFixYwB+36unpib///lulYuPMmTOoWbMm9PT0sHjxYrX5Q7548QIrV65EmzZtVH4fbdasGUaPHo2LFy9i4MCBMDIygpWVFX755RelN0bu3LkDQ0NDDBgwQCO+xtKTmBYsWKCW8mNiYqCvr6+2NfdrgglKNQrKyMhICIVC/Prrryovuyg+fvyIWrVqoW7dugX8m1SBooLy+fPn+Z6sRSKRxp6sb968yfuITZgwQS39Iit5TdazZs2Cj48PbG1tVWKy5jgOu3fvhrm5OczMzLBjx44CgSIPHz7E2rVr0bt3b343SF9fH15eXli4cCGuXr0qc1RtVlYWDh8+jCFDhqBChQogItjZ2WHq1Km4evWq3IuFOgXl+PHjoaWlhZiYGLWUXxgxMTHQ0tLChAkT5P5sVlYWtmzZwp/bXqdOHaxbty7f2FVEUHIchytXrmDKlCmoWbMm/wAxdOhQHDlyRGYfbLFYjCtXrmDhwoXw8vLizdfm5ubo3bs31q5di4cPHxYYfzt27ICZmRnMzc2xe/dumcdISSZza2tr1KhRAzo6OhCJRPDx8SnWdy4nJwe7du2Ch4cHn7M2PDxcIXN+YXz69Anjx4+HQCCAu7u72o/MffXqFdauXQsvLy+IRCKlLT1ubm4YPnw4/++EhARMnjwZFSpUgFAoRM+ePXHu3Dm553h6ejqcnJxQu3ZtlfW1LEybNg1CoRBnzpxRednnzp0DERVIbfU9wgSlmgTly5cvUbFiRbRp00bjaS9u3boFAwMDDB48WOVPgPIIyoSEBCxbtgxNmzbldxekvj8pKSkqbVdh5OTkIDg4GNra2qhduzYuXLig9jrzounE4FJev36NPn36gIjQvn17hIeHw8/PjxeuIpEIjRs3xvTp0xEZGamSQK7s7Gz8/fffGDZsGMzMzEBEqFatGiZOnIiLFy/KNA7VJSj37dsHIkJISIjKyy6JZcuWgYiwf/9+ma5PTk7G7NmzUbFiRT4tzYkTJwrtP1kFpUQiwYULFzBhwgR+DJibmyMgIADHjx9XSaqarKwsREZG4tdff0Xjxo0hEolARLC1tYW/vz9WrFiB9u3bg4jQt29flTxE5uTkYPPmzXywkLa2Np8FQh6T+YULF9CnTx+IRCKUL18eEyZMUFnGjAsXLqB27drQ1tZGcHCwRtICpaSkYOPGjYX6osu6u/iloJSSnp6OVatWwcHBgQ/a2759u0yuCBzHYdCgQTAwMNB44vHc3Fy0bt0alSpVUrkVjAnK/2CCUg2CUp2DV1a2bt0KIsKGDRtUWm5JgvLRo0dYvHgx/+Svq6uLrl27YuvWrRqNov7333/h7OwMkUiEX3/9Ve3R76pODK4oqampOHjwIAIDA2FjY5NvB2fcuHE4ePAgUlNTVV5vXnJzc3Hy5EmMHDmSDxqqWrUqgoKCEB0dXaR5UR2C8uHDhyhXrhx69OhRKrkiOY6Dr68vypcvX2x2gtjYWAwZMgQ6OjowMDDAqFGjSjShFScoJRIJoqOjERgYiCpVqvDpgX766SecOnVK7WlpPnz4gIMHD2LcuHG8/yURwcbGBoGBgTh06JDC4zAzMxObN2+Gs7Nzgd1bZUzmiYmJmDJlCkxMTCAUCtGjRw9ER0crPW4yMzMxbdo0iEQiODs749q1a0qVJw95s2Xo6OjInC2jKEEpRSKR4OjRo/xDgpWVFebOnVusO8n69etBRNi+fbtS30lRXr58iUqVKql8k4cJyv9gglINglKd2+vyEBAQAF1dXcTGxqqszMIE5b179zB//nw0aNCAN9v6+vpi586dahcvX6Lum7c6TdaKIN0Zmj59Opo0acLvDNnY2MDPz483bxMRvLy8VBotLwtisRhnzpzBmDFjYGVlxS8+o0ePRmRkZL4bu6oFZWZmJlxdXWFnZ1dqx2cCn8VVzZo14erqiszMTP51sViMv/76S+G0P18KSrFYjMjISIwePZrva2tra4wdOxZnz57VuKXk6dOn8PLyAhGhd+/eWLduHfz8/PgHHZFIhCZNmsi8U56cnIxZs2bxDymdOnUqcvf2S0oymdva2sLHxwezZs3Crl27MHfuXN6vtGHDhti2bZtKTjarX78+RCIRpk2blm8saIK8+Xyl312az/fLgzZKEpR5uXXrFgICAqCnpwc9PT0MGzasgIk/NjYWurq6GDFihMq+jyKoww2NCcr/YIJSxYLyyJEjanUAlofMzEy4uLigZs2aKltQpYIyPj4ewcHBqF+/Ph8R2rt3b+zZs0ejvjF5yWtemjNnjtLmpdIyWReHWCzG1atXsWjRIrRv35438ZmZmaFXr15Ys2YNHjx4UGCRPXr0KKpUqQIjIyOsXLmyVCIeJRIJzp07h6CgIH7XzNLSEiNHjsTJkycRHBysUkE5fPhwlT9QKYp0QR0+fDif9keamkfRtD8WFhaYM2cO/vnnH4wYMSLfbvDPP/+M8+fPl9rvvHLlShgZGaFq1ao4duxYvvc5jsODBw+wZs0a9OrVi3eR0NfXR/v27bFo0aJ8vryxsbEYPHgwv3s7evRolQRAlHSWebly5VCvXr18bgKzZ89WylyfnZ1dqm44Uj5+/Ig//vgDvXr14jM3SE8ci4+Pl0tQSnnz5g3mz5/P70h7eXnhyJEjePfuHWrWrIkGDRpoXEQXhqoDZZmg/A8mKFUoKKUpCjp37lxmUhRITX6+vr5KmW6kR+s1aNCAf7o1NjZG//79sW/fvlINdPnSAf7WrVtyl1FWTNZfwnEc7t27VyC61sDAAB06dJArujY1NRUjRowAEaFVq1Z48OCB2ttfFBKJBBcvXsTEiRNRrVo1/jvp6enh77//VvphYNu2bSAirF+/XkUtVp558+bxu9haWlro37+/QkmXs7OzcezYMejp6fEPFNWqVcOkSZNw6dKlUjHtS3nw4AFatmwJIsLIkSNlslBIsw0sWbIEHTp04AWOkZERL/CsrKzk2r1VlJJM5tL7gb29PSZNmlQgylxWpIGCAoEA48ePL/X7559//slnCJGO0QYNGuDGjRtyj6ecnBzs3LkT7u7u/O+or6+v9DndqkLVqfyYoPwPJihVJCjLchLVP//8U6GgBI7jcO3aNUybNo13wtbR0YGZmRkOHjxYJp4286boWLJkSYm7PGXNZF0YSUlJ2Lp1KwYPHszv5EkTS8+aNQtRUVFKmd9Onz6NGjVqQF9fH8uWLSv1s5KlCahbtmzJJ+s2MTHBkCFDcPjwYbn9X6VBaYMGDSpVcQXkT/sjnT/a2tpyn9KTlZWFQ4cOYfDgwXxEvUgkQqtWrfDvv/+W+vcUi8X47bffoK+vjxo1auD06dMKlZOamoolS5bwJntjY2PejaNKlSoYPHgwtm3bhqSkJBV/g+KRmswXLVoEd3d3/mEzr2+o1GQua2L2vKnMatasWeouUsBnq9aBAwdgZmbG+1w6ODhg2rRpuHbtmlzjjOM4BAYGgujziVoVKlTAxIkTNe52UxjSw0YaNWqktCsDE5T/wQSligRlWT/m6eeff5YpbQrHcbh8+TImT57Mm+RMTU3h5+eHo0ePwt/fXyNHL5aELEmEy6LJujDev3+P/fv3Y8yYMahduzbfPmdnZ4wfPx5HjhxReQL29PR0BAUFQSAQoHHjxvyZ0KXJvHnzYG5ujri4OEyfPj1fbsSBAwcWyI1YGB8/fkTt2rXh5OSE9PR0DbW8IIWl/Vm7di1ev34tc9qUjIwM7N+/HwMGDMiX83PGjBm4fv260nkoVcXt27fRqFEjCAQCBAUFKdTvDx8+RGBgIJ+0fcCAAbh8+TKAz3P9yJEjGD9+PO9iQ0SoXbu2Wk5skoWcnBxs374d9erVAxGhQoUKcHR05M338kSZ5z1sYdSoUWXisAU3Nzf4+/vjyJEjGDp0KExNTUH0+ZSsyZMn4/LlyyWKy7xps1SVdkiVXLp0SSXHITNB+R9MUKpAUO7ZswdEmjuIXhFycnLQpEmTQhM7SyQSxMTEYPz48bzDvLm5OYYPH44TJ07kMz9q6izv4pAec2ZoaIjw8HBIJJIya7IujMzMTJw8eRK//PILPDw8+F25GjVqICAgALt375YpMbkqOH/+PBwdHaGjo4N58+ZpJK1JUXwZlMNxHG7duoXZs2ejbt26vPmsb9++iIiIKCBcOI5D//791ZrYvyRkSfsTHx8PQ0ND9O/fv8AYTE9Px969e9GnTx8+0Xy9evXwv//9r0CqldIWlDk5OZg3bx50dHTg6OiI8+fPy/V5juMQGRkJHx8fCAQCmJmZ8Unbi+PVq1fYvXt3gTPlPTw88Msvv+DkyZMatZ58mXZoxIgR2LRpk1xR5hKJBOHh4TA0NISNjY3aju2UlS99KHNycnDixAkMHz6cd0OwsbHB+PHjERMTU8DlRprYv1mzZvnuKcqkHVIHYWFhICKlThhjgvI/mKBUUlDeu3cPxsbG6N27d6mbnUoiMTERZmZm+OGHH5CTk4OoqCiMGzeOPzWiYsWKGDVqFE6fPl3kTl1pCsr3799j6NChvAP5uHHjyqTJ+kvEYjEuXbqEefPmoW3bttDV1eUDUvr27Yv169fj8ePHpda+zMxMTJ06FUKhEK6urqUWxFJSlPedO3cwd+5cftdPX18fPXr0wO7du5GWlobVq1eDSL1HjxZFXFwchg4dKnPan507d4KIsHr1aqSlpWHXrl3o0aMH7xPp6uqKefPmFVtGaQrK2NhYuLq6QiQSYerUqXIJuOLS/ijC48ePsX79evTt25cPTNLV1YWnpyfmz5+PS5cuacSto7i0Q7JGmY8bN47f9Rw6dKjGd16lFBeUk5ubi9OnT+Onn37iH5wqV66McePGISoqCjk5OSUePapI2iF1wHEcevXqBWNjY4WPymSC8j+YoFRCUGZkZKB+/fpwcHAoE2aKksjNzcWiRYv4nZ4vbwSy3HQ1KSjzmqy7dOnC+/TkNVl7eXlh0qRJ2LFjB27fvl0qJusv4TgOt2/fRlhYGHx8fHgzu5GRETp37oyQkBCFnN3VzZUrV1CvXj1oaWlhxowZas/d+SXypA168OABFi5cCDc3N15ACAQCtGvXTmMpgpRJ+/Phwwd4enpCKBTyO+nu7u5YtGgRHj58KFP9pSEos7KyMGPGDGhpaaFevXq4cuWKzJ/9Mu1PcUnbFUUaPLhs2TJ06tSJv8+VL18ePj4+CA8PR3x8vFrnXnp6OlavXl1i2qGSosylPrddunSR+yxzZZE1ylssFuPs2bMYO3YsH90t7XNZj52UJe2QOklNTYW9vT3q169foktNYTBB+R9MUCohKP38/MpU9Fph5DVVWFhY8D5pAoEAYWFhckejq0tQFmeylv5ZWVlh8uTJOHLkCJKSksqUIEtMTMTmzZsxcOBAPqBAW1sbrVq1QnBwMM6fP1+q5mRZyc7OxqxZs6ClpQUnJyeN+gQrmocyLi4OpqamvIlYR0cHnTt3xpYtW9QSFaxo2p+3b99i8+bN6NSpE/9wZGhoCFNTU8TFxcndDk0LykuXLsHJyQlaWlqYPXu2zOLmy7Q/siRtVxU5OTk4f/48goOD0bJlS/6eYmVlhYEDB2Lz5s1ITExUS90SiQTHjh3DDz/8ACJCpUqVMGfOnGLTDuWNMp80aRIqVaqU7x5Y0lnmqkKRtEESiQRhYWEQCAS8z6+FhUWhrlOFUVTaIU1kTLlx4wb09fXh5+cn92eZoPwPJigVFJSbN28GEWHLli1qapniZGdn4+jRo/Dz8yvUmTo3Nxft2rWDpaWl3NGSygpKWaOsAwICMGzYMFSoUAEmJibYtm1bmRKQb9++RUREBH766SfeR0ogEKBBgwaYNGkS/v7771INClGW69evo0GDBhAKhZg0aZJCT+7yooig5DgOPj4+MDExwZMnT5CYmIjQ0FA0b94cAoEAWlpa6NChAzZs2KC0Oe3Ro0cICgriA0dkSfvz5s0brF+/Hj/88AO0tLQgEAjQokULLF++HM+ePcPjx49RoUIF+Pj4yD2+NSUoMzIyMGnSJAiFQjRs2BDXr18v8TNisRj79+9Hq1ateH+7JUuWqD3tT0mkp6fj77//xqRJk9CgQQMIBAI+kvmnn35CRESEWrJ03L59GyNGjIC+vj50dXXh7+8v00YEx3HYunUrKlSogAoVKsDf37/ExOyyRpkXhyKCMikpCZaWlvDy8kJubi4uXbqESZMmoXr16gWCO4t7GPky7ZCDgwNWrFihdtcl6Zq+efNmuT7HBOV/MEGpgKCUPs34+/ursWXykZmZiYMHD2LQoEG8idXe3r7IdA+vXr2CtbU1WrZsKZeZWB5BKUuUdWEm65cvX8LX1xdEBF9f31I7vjIvnz59wvHjxzF58uR8C5G9vT1GjhyJvXv3auR8ck2Sm5uLBQsWQFdXF/b29oiOjlZrfYoIyiVLloCIcOjQoQLvJSUlYcWKFWjdujWEQiFEIhHatWuHNWvWIDk5Waby86b9EQgEMDU1LTFwJDk5GatXr4anpydEIhGEQiHatGmDlStX4sWLFwWuP3jwIIgIS5Yskf2LQzOCMjo6Gvb29tDV1cXChQtLvFekpqYiJCSEFxHNmjXD3r17y4QrSmGkpKRg7969GDlyZL4Hw4YNG2Ly5Mk4fvy4SnNEpqSkYMGCBbzfuqenJw4dOlTiLtzLly/RvXv3fPfEkkzmskaZF4a8gjI3NxctWrRA5cqVC+zAchyHf//9F7/88gvs7Oz4tg0aNKjY9HMcxyEmJga9e/fmA57UnXZIEasjE5T/wQSlnIJS6m/h7OyskV2b4sjIyMC+ffvQv39/GBsb8w7uM2fOlMlHLzo6GiKRCFOmTJG5zqIEpaxR1vPmzSvSZC19GjcxMYGFhQX27t0rc7tUTV5TWatWrXgTZaVKlTBgwABs3rxZJUlxvwbi4+PRpEkTCAQCjB07Vm07BfIKyqioKJnHb3JyMtasWYN27drxIq9169ZYsWJFobv0haX9KS5wJCkpCeHh4WjVqhUEAgFEIhG8vLywdu1amSL2J0+eDJFIJJdoV6eg/PjxI8aOHQuBQIAmTZqUuFgWl/bnayIhIQGbNm3CgAEDeHOzjo4OWrVqhTlz5iAmJkYl4jgnJwe7du2Ch4cHiAh2dnYIDw8vdm5xHIc9e/bAwsICJiYm2Lp1a6H3UEXPMs+LvIJSOn5LWkc5jsP169cxY8YMPkVa3gMyilpTNZV2KG9chKzHBjNB+R9MUMohKPNGhH159qmmSE9Px549e9C7d2/eZ0x6ZNaXaUVkYfHixUXu8BRGQEAA6tevr/LE4ImJifD29gYRYcCAAaUS7Xfjxg2EhISgc+fOvEAvV64cfHx8EBYWhtu3b5cps7smEYvFCAkJgb6+PqpVq4aTJ0+qvA55BKWiO+zAZzP0hg0b0KFDB94M3bx5c4SGhuLff//Nl/anY8eOOH78eKG/e2JiIkJCQtCsWTPevN6xY0ds3LhR7t1q6Q6PtbW1zCmj1CUoT548iWrVqkFfXx+hoaFFBuspmvbnayFvcF3Xrl15v0BjY2M+uO7mzZtK3xO+TDs0YcIEPHnypMjr37x5g/79+/OBTUVFUudFnrPM9+/fj/r16yMgIECm9h84cABEhKVLl8r6lXlu376N//3vf3xku6GhIX+Eb2EuQ5pIO3T//n25MrcwQfkfTFDKISilOasiIiI00LL/SE1Nxc6dO+Hr68unFWnQoAHmz5+vcKoDKRzHoWvXrrwPWl4KM1nnjbRWRZQ1x3FYu3YtjI2NYW1tjYMHDyr1feThyZMn2LBhA/r165cv3Ujbtm0xb948XLx4scya6kqLhw8f8lHNw4cPV2lEtayCUiwWw9PTE5aWloWakOXh3bt32LJlS75TeoRCIZo0aVKoaH78+DGWLFmCRo0a5YvC/f3335X2D5T6oLVr106mjAuqFpQfPnxAQEAAiAitW7cuMtpc1Wl/vhZyc3Nx8eLFAum/KlasiH79+mHDhg3FCsGSKC7tUGEcOHAAVlZWKFeuHNatWye3sC3JZC7dmS3OZC71Ae7WrZvSwvru3buYN28eXF1d+bRgvr6+2LlzZ4EsKupOO7R3714QyZZbmgnK/2CCUkZBefHiRZVk1ZeV9+/fY+vWrejatSt/4/Lw8MDixYvx6NEjldb17t072NjYwNHREUuWLCnUZG1vb49evXrB3d0d9vb2KomyfvToEdq2bQsigr+/v9pzrr1+/Rp//PEHhg8fni8hsru7O6ZOnYp//vmn1N0YvgYkEglWr14NY2NjVKlSBUeOHFFJubIKypkzZ0IoFMp9fOGXiMViHDhwAG3atAERwdraGn379oW3tzc/59zc3DBx4kRMmDABDRs25Hfhu3fvjh07dshsFpOVkydPQiAQYNasWSVeq0pBefjwYVSuXBnGxsZYs2ZNoT59mkj78zWRkZGBf/75B1OnTuXP5SYi1KxZE8OHD8cff/yhkMCRNe0Q8Hmd8PPz4/0xlc1nKzWZ29vbw93dvViT+ZIlS+Do6Ihq1aqp/N798OFD/phL6YN+165dsXXr1gJ1qSvtkKyn3zFB+R/fvaC8fvsutC2rY+uRKNxK+oD0rII7UtJzPxs3bqzWPGBv377F77//jm7dusHY2Bh6enpo3bo1li9frjJ/vZKirEUiEdzd3REQEICVK1fi/Pnz/NNhelYuBoyeAlev7kX2lSxI00sYGBjA1tYWJ06cUMl3+5KPHz/yR7ZJd1OIPh9fN3r0aOzfv7/Uo06/ZhISEviUKIMGDVIqOjY9KxcT54bCqm6TYsfW8ePHIRAIMGfOHIXrypv2x8LCAp06dcJff/2VL61JbGwsAgIC4ODggEqVKqFSpUpwdHTE8OHDFUrxIw/BwcEQCATFnpaSnpULqzru+HnucqXm4tu3b/Hjjz+CiNChQ4dC7zOlmfbna+Ldu3fYt28fRo8ejVq1avH3G2dnZ0yYMAFHjx6Vy/9YnrRD0tPDDAwMFEoHl5f0rFw08OyKfmN+4cdWYSZz6Rnr6ogyz0tCQgKWL1+OVq1aQU9PD8bGxujWrRt+//33fPecN2/eYPHixahRowb09PTg7e2No0ePKtwX2dnZaNSoEWxtbYu8t6Vn5WLX39HQsXLA0Qs3FJ6H3woCAKDvjAevPtKOS4kUee81Jb7LoLwdICAiG1MDauNoSQMa2VBNC0Pq0qULXbx4kWJjY8nGxqa0mi03OTk5FB8fT3Fxcfn+UlNTiYjIwsKCXFxc+L+7d+/SnDlzaPfu3dSnTx8ikq+v7Csal9im+/fvk5+fH50/f55Gjx5NCxYsIGPjkj8n6/e9dOkSnTp1ik6dOkUXL14ksVhMlStXpnbt2pGnpye1bduWKleurJL6GEQAaOvWrRQUFES6urq0evVq6t69u0yflXdsPX/+nFxdXcnNzY2OHDlCQqFQrrY+fvyYwsPDqVGjRtS9e3fS0dEhgUAgVxmagOM48vb2pn///ZdiY2OpSpUqRKT6ubhv3z4aNWoUZWdnU2hoKA0aNIjvD4lEQocOHaLQ0FA6e/Ys2djY0JgxY2jYsGFkYmKihm/97ZGUlESnT5+mkydP0qlTpygpKYm0tLSocePG5OnpSe3atSMPDw/S0dEpsaz4+HgKCwujrVu3EsdxNHDgQAoMDKR69erx13z8+JGmTp1Kq1atoubNm9PGjRvJwcFBprbKO7Z2795N/fr1o1mzZpGDgwO/tsTGxlJKSgoREZUvXz7f+uLi4kJ16tSR6fuqGolEQgBIS0tLrs8lJiaSq6srNWnShA4ePEhCoVDl8/Bb4rsSlM/eZdC0/Tcp+mEKiYQCknBFf3Xp+1W0PtKl8CA6uGszdezYUYOtlQ/pz3jv3j1atGgRxcbGUnx8POXm5pJAICA7O7sCk9vKyirfggqABgwYQIcOHaLDZy7Shrh0ufqqhZ05ze9ej6qaGhS4RiwWU0hICM2cOZOqVKlCGzdupJYtWyr1nTmOoxs3bvACMioqij59+kQmJibUpk0b8vT0JE9PT3JwcCiTwuFb4uXLl/TTTz/RgQMHqHfv3hQeHk6WlpaFXqvIPGxe04we7AqmF/dvUmxsLJmbm8vULgAUFRVFoaGhdODAAYqKiqLmzZsTgDI9JlJSUsjV1ZVsbGxox19/04yD8Sqbi69fv6YxY8bQ3r17ycfHh1avXk1WVlZERJSWlkabNm2isLAwevLkCTVr1oyCgoKoW7duci/GjP8AQPfv3+fvVadPn6YPHz6QoaEhtWzZkr9X1a9fv9gHpbdv39L69etpxYoVlJSURJ6enhQUFETe3t78586ePUv+/v6UlJREwcHB9PPPPxf52ykyFxtY69PJBf7UtW0z2rZtW4E15OXLlwU2MR48eEA1a9akc+fOkbm5eamMJbFYTFpaWvT27VsyMzOT+XPHjh0jb29v+nX+MkqwbKqyefgt8t0Iyt1XEmnWwdsk5lDsQCgAOBIJiOb5OlNfd8V3JzW5gI0ePZpyc3N54VivXj2ZdwHT09Optd80SrVvTxwJ5eorkVBAWkIB/a+rU76+unXrFvn5+dG///5LP//8MwUHB5OBgfwTDAA9fvw43005JSWF9PT0qEWLFvxN2dXVlUQikdzlM5QDAO3Zs4fGjBlDACg8PJz69u2bb9wrOg9FAiKJOJeGN6xA0/q0LvH67Oxs2r17N4WGhlJcXBzVrl2bpkyZkm8XTt0oO+cvXLhA/vM3ksSlh/z9VchcBEC7du2icePGkUAgoBUrVlDv3r1JIBDQo0ePKDw8nDZt2kSZmZnUp08fCgwMJHd3d4XbzygaiURCsbGx/L0sOjqasrKyyNzcnNq2bcvfy2rUqFHoGMrNzaU///yTQkJC6PLly2RnZ0eBgYE0ZMgQMjIyooyMDJoxYwaFhISQm5sbbdq0ierWrZuvDEXnopBAkIhpVhcnGtLCXqbPfPz4kbKyssjMzExuy4IqAUDZ2dk0bNgw+umnn6hp06YyzdHBwesoOqMSCURaKlkTv1W+C0G5IvIBLT1xX+lyJrZ3oDFtZJtARJ+3y/ft20cjRowgfX19peuXBWUXMVX21fBmtrRw4UKaO3cu2dnZ0aZNm6hx48ZylfPq1Sv+pnvq1ClKSEggkUhE7u7uvNmoSZMmpKurq3SbGarhzZs3NHbsWPrjjz+oa9eutHr1arK2ttbIPHz16hWtWbOGVq9eTa9evaKOHTvSuHHjqHz58qSjo0MNGzZUun55uHbtGuXm5pKHh4fc81KV/dXdwYB++uknOnToEPXt25fCwsLI3Nyczp49S6GhoXTw4EEyNTWlESNG0KhRo5hbiIbJysqiCxcu8Pe5K1eukEQiIVtb23zuOhUrVizw2YsXL1JoaChFRESQkZERDRs2jMaMGUPVqlWjixcvkp+fHz18+JBmzJhBU6dOJW1t7VJbE8sKY8eOpRUrVpCbmxsFBQVRr169ijTFf+99JQ/fvKDcfSWRpu67qbLyFvnWoz7FPGk8fvyY/vzzT4qIiKDLly9T1apVKTExUWX1qxNV95X+jT/pwfGtNHXqVJoxY4ZMoi8tLY3Onj3L31hv3bpFREROTk68gGzZsiWVL19eZe1kqIf9+/fTqFGjKDMzk4Yv2kJ7nmqrrOwv5+H169dp+fLltGPHDtLS0qJBgwZR8+bN6cqVK/Tnn3/S8+fP6caNG1S3bl2N7lDeunWL6tevT1WrVqUePXpQz549qUmTJiXu0qh6LmZEriNRwmVavXo1dezYMd/ubZ06dSgoKIgGDBigkOWAoXpSU1Pz3Qdv375NRER169bNdx8sV64c/5lnz57RypUrad26dZSamkrdu3enoKAgatiwIc2dO5cWLVpEdevWJf/5G+m36GSVtbWkNbGsIRaLKTo6mp48eUJ//PEHnThxgqysrGj06NE0YsSIfO40mtYPXzvftKB89i6D2oWcpWwxp7IydbWEdPLnVvl8Iu7fv8+LyGvXrpGenh55e3tTz549qXPnzioLOlEnqu8rkEAiptVdKlOHFkWbzbKzs/M9mV++fJkkEgnZ2NjkezKvVKmSitrF0CTv37+nMVNm0QXTdsQJVOeGoKslpOPjmtONC5EUGhpKkZGRVLlyZerUqRNJJBI6evQovXz5kqytrXkh17x5c42b2ziOo+joaIqIiKA///yTXr58SVZWVvna9KV7hsrnIkBC4mhzzxp05siftGrVKnr9+jV5e3tTUFAQtWvXrkz7kzKIkpOT8wX4JCYmkkgkIg8PD948LrXUfPr0ibZt20ahoaF07949atiwIQUFBZG9vT1NmLWAkhsMIzFU93sXtiaWZcRiMc2ZM4eCg4OpQYMG1KJFC3r58iUdPHiQiIgPeCpvXUMj+uFb4psWlD9uvEQxj9/K5zNZAiKhgJrWMKNpTctRREQERURE0I0bN8jAwIA6d+5MPXv2pI4dO5KRkRFlZ2fTgwcPCviulEXU2Vfb/Bvxr0kkEoqLi8vnO5SZmUlmZmb5fIdq1qzJFrlvBHWMLaGAiHt5lxK2TKTatWtT5cqV6caNG/T69WuqWrUq9ezZk3r27EmNGzcuVZ+tvHAcRxcuXODvG8+fPydLS0vy9fWlnj17UqtWrUhLS0st/SUgUObT6/Tx4HwaMmQIjRs3jhwdHVVWPkNzAKBHjx7l8yV/+/Yt6evr5/Mlr1+/Pp06dYpCQ0Pp+PHjVKlSJWowYRPdfS9nHEEJFHafL+tkZ2fTgQMHKCIigo4cOUIZGRlUp04dsra25u8jTmNWU2Y5m+++r+ThmxWUD159JK/QKLWVn7R+JOnnpFKXLl2oZ8+e5OHhQQ8ePMgX2RYfH0+Wlpb0/PlzmcqsVq0aBQUFUVBQEP/amTNneMfrtLQ0sre3p0mTJtGAAQNU9l3U3VcbutvSg3+j6eTJkxQZGUnv378nAwMDPrqxXbt2JUY3Mr5O1D220nZNovcJd6h69eq8iHR3d1f6YaSwuTh79mz63//+V+BaAwMD+vTpk1zlcxxHV65c4cXl06dPyczMjHr6j6W/hW5Ktb04/vR3oYZ2zD/yW4LjOLp+/Xq+bBcZGRlkYmLCP6Tb2trSnydj6JRuE7W14+TPLcnOUn3WuKdPn1L16tUpNjaWXFxc+Ne3bNlCQ4cOzXetrq4uZWVlFVpObm4uHTx4kJ49e0YuLi5kb29Ply5dooiICDp06BClp6dT5TpupNV1ttq+i7r7qrT4ZvNA7LiUWGJov8KAo7YBs8hd9JRu3bpFP//8MyUkJBARkZ6eHtWrV488PDxo+PDh5OHhoVRVMTExVL9+fZoyZQpVrFiRDh8+TIMGDaLy5ctT586dVfFt1N5XvX8Np49nNlGjRo1o7Nix1K5dO2rUqFGp5CNjaBZ1ji0BOHLr9zMt7NWQXF1d1b6jPXHiRBo5cmS+1zw9PRWKhBYKhdSoUSNq1KgRLV68mK5du0YRERF0LsOEREbq6S+RUECH4j8wQfmNIRQKydXVlVxdXWnixImUk5NDFy9e5AXmuHHjSCwWk7PfXBJVUt/Y2n4xkWZ3dVK6rNatW9OQIUNoyJAhMn+mXLlydO/ePf7fxd0LhEIhvX79mn755RdedNra2pKLiwsFBgYSx3F08r0JvSEQSPX3FFX2VVnjm92hbLUkkhLeZait/Nx3Lyh3/68Fcjs6ODgolGOrdevWdPbs2XyvFfXTdOrUiSpWrEibNm1SqO1fou6+stAjOj2+5VfhS8pQLeoeW7ZmBnR2YhuVlinrXLx+/Tq5uLhQVFQUtWjRQiV1f439xSjbfPz4kaKjo2nmFVBK4Zt2KkFVY6soQfmlSGzVqhWdOXOGtmzZQkFBQfThwwe56hGLxXT//v18VkVpYnbrEetJ28RKyW9SNN/qPPwmdyjTs8WUqMabMhGRjqk13UtMIiM91USu7tu3j5ydnWn48OEUEBBQ7LWpqalUu3ZtldSrib5KySIS6mgmbRKj7KCJsZX4NoM+ZYvJUFd1tzJZ5+KGDRvIwcFBZWLya+0vRtnG2NiYWnq2p7fRx9Vaj7rH1uXLl8nDw4NOnjxJTk5O+Sxc6enpZGtrSxzHUYMGDWj+/Pnk5FT8DqCWlhbVqVOH6tSpQ/379yeizw+ODxOek9faG2r5DlK+1Xn4bX2b/yfh7SdS97YriMiyhhPlvnlS7HWVK1emp0+fllieqakpiUQiMjY2Ljaiec+ePXTlyhVau3ZtkdecPXuW2rVrV2KdRETaFtXJcnCITNcqCojIonqdEvuK8W2hqbFlYuNAua9LHls3b94kJyenEk3jsszFrKws2rFjB02dOrXotgF0+/btfMfjFYe2ZXWy9guX6VpFYXPx+6S07/NVq1alx48fK1W+hYUFERGZmZnlm5eOjo60adMmql+/PqWmptLSpUupadOmdPv2bf7Y0rzk5uZScHAwLVy4sNB6NNVXT99+Iifrbyv93TcpKHNUGOZfHE71nUnno0Wx10gnwZfs2LGDRowYwf/72LFjJdYXGRlJQ4cOpfXr1xf79GVsbCyz72aOsTW9kelK5ZClrxjfFpoaW5ZW1kTaOSVeV5QriiJzcf/+/fTx40caPHhwsddpa2vLnCRcYK4Z30Y2F78/Svs+X1hCdinz58+n+fPn8//OzMykixcv0pgxY/jX4uPji/x8kyZNqEmT/4KNmjZtSrVr16a1a9fSnDlzClwvEAioSpUqRa6RmuorTekUTfJNCkodLc1EC2/ZtEHhJ4yuXbtSo0b/pQ4oadE5e/YsdenShUJCQmjQoEHFXtugQQM6f/68TO24/SKVOoWfk+laZVCmrxhfJ5oaW8ePHlFqbMk7F4k+m7s7d+5c7EIpEAjI0dFR5iwPbC4y1EVZHlsjR46k3r178/8eMGAA9ejRg3x9ffnXrK2tZZ5H2tra5OrqSg8fPiz0fS0tLRoxYkS+h8i8aKqvNKVTNMk3KSirmRmSgEitZm/B/9ejKMbGxgWCVHR0dEgikRS49syZM9S5c2datGgRDR8+XOE6C+Nr6CvG18nXMrbkmYtERE+ePKHIyEg+EbKq+Fr6i/H1UZbHlqmpKZmamvL/1tfXJ0tLS7Kzs8t3ndRnsqh5KUUikdDNmzfJ29tb7rYQle2+Kut8exKZiAx1tchGzZnobcwMVO5QW61aNYqKiqKkpCRKSUkhos9m7k6dOtG4ceOoR48elJycTMnJyfTu3TuV1Pm19hWj7PM1j63C5qKUTZs2kZWVFXXs2FGldX7N/cUo23wLY8vS0pL09fXp77//plevXlFqaioREQUHB9OJEyfo8ePHdO3aNRo4cCAlJCTQsGHDFKrnW+ir0uKbFJRERG0cLUkkVE9eOpFQQG0cLFVebnBwMD19+pRq1qzJ+17+/vvvlJGRQQsWLCArKyv+L685QFm+xr5ifB18rWOrsLlI9DmJ9JYtW2jIkCEFjkxUBV9rfzHKPl/72NLS0qKwsDBau3YtWVtbk4+PDxF9Pt41ICCAateuTd7e3pSWlkYxMTFUp04dhev62vuqtPhm81Cq+4SObynTPesrhrpgY0s+WH8x1AUbW7LD+koxvtkdSvuKxtTCzlzlTxkioYBa2Jl/U4OB9RVDXbCxJR+svxjqgo0t2WF9pRjfrKAkIprfvR5pqXhAaAkFNL+7bHnlviZYXzHUBRtb8sH6i6Eu2NiSHdZX8vNNC8qqpgb0PxWflxnc1YmqqtlhtzRgfcVQF2xsyQfrL4a6YGNLdlhfyc83LSiJiPq629DE9g4qKWtSe0fq426jkrLKIqyvGOqCjS35YP3FUBdsbMkO6yv5+GaDcr5k95VEmnXwNok5kIST/SuLhALSEgoouKvTNz8YpLC+YqgLNrbkg/UXQ12wsSU7rK9k47sRlEREz95l0LT9Nyn6YQqJhIJiB4b0/RZ25jS/e71vepu6MFhfMdQFG1vywfqLoS7Y2JId1lcl810JSikPXn2kHZcSKfL+a0p8m5EvI76APicdbeNgSQMb23yz0ViywvqKoS7Y2JIP1l8MdcHGluywviqa71JQ5uVTtpievv1EOWKOdLSEVM3M8JvMYK8KWF8x1AUbW/LB+ouhLtjYkh3WV/n57gUlg8FgMBgMBkM5vvkobwaDwWAwGAyGemGCksFgMBgMBoOhFExQMhgMBoPBYDCUgglKBoPBYDAYDIZSMEHJYDAYDAaDwVAKJigZDAaDwWAwGErBBCWDwWAwGAwGQymYoGQwGAwGg8FgKAUTlAwGg8FgMBgMpWCCksFgMBgMBoOhFExQMhgMBoPBYDCUgglKBoPBYDAYDIZSMEHJYDAYDAaDwVAKJigZDAaDwWAwGErBBCWDwWAwGAwGQymYoGQwGAwGg8FgKAUTlAwGg8FgMBgMpWCCksFgMBgMBoOhFExQMhgMBoPBYDCUgglKBoPBYDAYDIZSMEHJYDAYDAaDwVAKJigZDAaDwWAwGErBBCWDwWAwGAwGQymYoGQwGAwGg8FgKAUTlAwGg8FgMBgMpWCCksFgMBgMBoOhFExQMhgMBoPBYDCUgglKBoPBYDAYDIZSMEHJYDAYDAaDwVAKJigZDAaDwWAwGErBBCWDwWAwGAwGQymYoGQwGAwGg8FgKAUTlAwGg8FgMBgMpWCCksFgMBgMBoOhFExQMhgMBoPBYDCUgglKxv+xd9dhUaVvH8DvmaFDEUEFUXFFEBEFxS4Q7FbUtQu7YO31Z2In9irm2q1rrY2KXaDYjV0oIRIz5/v+4TtnRWqGmQHU+3NdXLvC4ZxnHk7c54n7YYwxxhjTCAeUjDHGGGNMIxxQMsYYY4wxjXBAyRhjjDHGNMIBJWOMMcYY0wgHlIwxxhhjTCMcUDLGGGOMMY1wQMkYY4wxxjTCASVjjDHGGNMIB5SMMcYYY0wjHFAyxhhjjDGNcEDJGGOMMcY0wgElY4wxxhjTCAeUjDHGGGNMIxxQMsYYY4wxjXBAyRhjjDHGNMIBJWOMMcYY0wgHlIwxxhhjTCMcUDLGGGOMMY1wQMkYY4wxxjTCASVjjDHGGNMIB5SMMcYYY0wjHFAyxhhjjDGNcEDJGGOMMcY0wgElY4wxxhjTCAeUjDHGGGNMIxxQMsYYY4wxjXBAyRhjjDHGNMIBJWOMMcYY0wgHlIwxxhhjTCMcUDLGGGOMMY1wQMkYY4wxxjTCASVjjDHGGNMIB5SMMcYYY0wjHFAyxhhjjDGNcEDJGGOMMcY0wgElY4wxxhjTCAeUjDHGGGNMIxxQMsYYY4wxjXBAyRhjjDHGNMIBJWOMMcYY0wgHlIwxxhhjTCMcUDLGGGOMMY1wQMkYY4wxxjTCASVjjDHGGNMIB5SMMcYYY0wjHFAyxhhjjDGNcEDJGGOMMcY0wgElY4wxxhjTCAeUjDHGGGNMIxxQMsYYY4wxjXBAyRhjjDHGNMIBJWOMMcYY0wgHlIwxxhhjTCMcUDLGGGOMMY1wQMkYY4wxxjTCASVjjDHGGNMIB5SMMcYYY0wjHFAyxhhjjDGNcEDJGGOMMcY0wgElY4wxxhjTCAeUjDHGGGNMIxxQMsYYY4wxjXBAyRhjjDHGNMIBJWOMMcYY0wgHlIwxxhhjTCMcUDLGGGOMMY1wQMkYY4wxxjTCASVjjDHGGNMIB5SMMcYYY0wjHFAyxhhjjDGNcEDJGGOMMcY0wgElY4wxxhjTCAeUjDHGGGNMIxxQMsYYY4wxjXBAyRhjjDHGNMIBJWOMMcYY0wgHlIwxxhhjTCMcUDLGGGOMMY1wQMkYY4wxxjTCASVjjDHGGNMIB5SMMcYYY0wjHFAyxhhjjDGNcEDJGGOMMcY0wgElY4wxxhjTCAeUjDHGGGNMIxxQMsYYY4wxjXBAyRhjjDHGNMIBJWOMMcYY0wgHlIwxxhhjTCMcUDLGGGOMMY1wQMkYY4wxxjTCASVjjDHGGNMIB5SMMcYYY0wjHFAyxhhjjDGNcEDJGGOMMcY0wgElY4wxxhjTCAeUjDHGGGNMIxxQMsYYY4wxjXBAyRhjjDHGNMIBJWOMMcYY0wgHlIwxxhhjTCMcUDLGGGOMMY1wQMkYY4wxxjTCASVjjDHGGNMIB5SMMcYYY0wjHFAyxhhjjDGNcEDJGGOMMcY0wgElY4wxxhjTCAeUjDHGGGNMIxxQMsYYY4wxjXBAyRhjjDHGNMIBJWOMMcYY0wgHlIwxxhhjTCMcUDLGGGOMMY1wQMkYY4wxxjTCASVjjDHGGNMIB5SMMcYYY0wjHFAyxhhjjDGNcEDJGGOMMcY0wgElY4wxxhjTCAeUjDHGGGNMIxxQMsYYY4wxjXBAyRhjjDHGNMIBJWOMMcYY0wgHlIwxxhhjTCMcUDLGGGOMMY1wQMkYY4wxxjTCASVjjDHGGNMIB5SMMcYYY0wjHFAyxhhjjDGNcEDJGGOMMcY0wgElY4wxxhjTCAeUjDHGGGNMIxxQMsYYY4wxjejldAFy2udEOT358JmS5AIZ6EnJPr8pmRr+8tWSJq4rpit8bqmH64vpCp9bquO6SumX/OT338TShguRdOLuW4qMiid88zMJERW1NCEvpwLUsXJRKlnQPKeKmStwXTFd4XNLPVxfTFf43FId11X6JACQ+WY/h2dR8fTnrht0+sF7kkklpBDS/+jKn9d0sKKpLV2piKVJNpY053FdMV3hc0s9XF9MV/jcUh3XVeZ+mYBy86VIGv/PTZILyPBE+J5MKiE9qYQmNnOh3ysW1WEJcw+uK6YrfG6ph+uL6QqfW6rjulLNLxFQLjpxn2YfvqfxfobVc6SBXiW1UKLci+uK6QqfW+rh+mK6wueW6riuVPfTz/LefClSKycDEdHsw/doy6VIrewrN+K6YrrC55Z6uL6YrvC5pTquK/X81AHls6h4Gv/PTa3uc9w/N+lZVLxW95kbcF0xXeFzSz1cX0xX+NxSHdeV+n7qgPLPXTdIrsZ4B1XIBdCfu25odZ+5AdcV0xU+t9TD9cV0hc8t1XFdqe+nDSjvv4ml0w/eqzWAVhUKAXT6wXt68DZWq/slIrK3t6egoKAU3wsJCaHmzZuTjY0NmZqakpubG23YsEGrx/0R64r9GH6Gc+vJkyckkUgoLCwsxfc9PT1JIpGk+mrcuHGWj/Uz1BfLnX70cyu963DNmjWprkEjIyONjvWj11VO+WkDyg0XIkkmlehk3zKphNafz56xEGfPnqWyZcvSjh076Pr169S9e3fq0qUL7du3T2vH+FnqiuU+P9K55enpSWvWrFF5+507d9KrV6/Er4iICJLJZNSmTZssl+FHqi/2Y/lRzi11r0Miojx58qS4Fp8+fapRGX6UusptftqA8sTdt1p/u1BSCKAT995qdZ+enp709OlTCggIEN+yiIj+/PNPCgwMpGrVqlGJEiVoyJAh1KBBA9q5c6fWjv2j1RX7cfwM51bx4sWJiMjd3Z0kEgl5enoSEZGlpSUVKlRI/Dpy5AiZmJhoFFD+DPXFcqcf/dxK7zokIpJIJCmuxYIFC2p0rB+9rnLKTxlQxiXKKVLHA18jP8TT50S51va3c+dOsrOzo0mTJolvWemJjo4mS0tLrRz3R6wr9mP4Wc6tixcvEhHR0aNH6dWrV+m+zK1cuZJ+//13MjU1zdJxfpb6YrnPz3BuZXQdxsXFUbFixahIkSLUvHlzunkz65Npfoa6yik/5dKLTz98Jl0n1wQReTZtQwafM37TsLa2pt27d2e6P0tLS5LJZGRubk6FChVKd7utW7fSpUuXaNmyZeluc/XqVRo0aFCmxyQiSjItQKjgp9K2WaVqXbGfS3adW04eNYg+Pk/z5w8ePNB4PJW1tTUREeXPnz/da/PixYsUERFBK1euTHc/CQkJ5ODgkO7PJZZFSNb4fxqVNTN8Lf6acvo+X7BgQY171dK7Dp2cnGjVqlVUtmxZio6OptmzZ1O1atXo5s2bZGdnl2o/crmcVq5cSX///Xeax8muunry4TO52ObV6XGy208ZUCbJhWw5zs3bdyn59f0MtylcuHCa39+wYQP16dNH/PfBgwczPd6JEyeoe/fuFBwcTC4uLuluFxsbK77NZUa/UEkqUEGlTTWiSl2xn0t2nVvvPnykpFcv0vxZRus2TJ06laZOnSr++8uXL3T+/HkaOHCg+L1bt26pVIaVK1eSq6srVapUKd1tANCLF2mXk4jIQDAlG5WOphm+Fn89OX2fL1KkSLq/o+l1WLVqVapatar472rVqpGzszMtW7aMAgMDU20PgJ4/f57uMzK76iq74pTs9FMGlAZ62dOTf+n8OXIpnLU3jGbNmlHlypXFf6cXeCqdPHmSmjZtSvPmzaMuXbpkuG3t2rUpOTlZpXLcfBlNjReGqrStJi5dOPfTvY2xjGXXuXX18sUsnVt9+/altm3biv/u2LEjtW7dmlq1aiV+z9bWlp4/T7v1U+nz58+0efNmmjRpUobbGRsbZxjg8rXIdCU3n1vaug6V9PX1yd3dnR48eJDuzwMDA9MNNkPCH1D3LdpJZp6R7IpTstNPGVDa5zclCZFOu70BkKeHC7mVcSY3Nzfxy8nJifT0Mq9Wc3NzMjc3T/E9AwMDUigUqbYNCQmhJk2a0IwZM6h3795a+wxE2VNXRERWhj/9Cp/sO9lxbkn+/zhZYWlpmWIssrGxMRUoUCBVt7SBgQERUZrXJhHRtm3bKDExkTp16pSlcijl9vpiP6bY2Fi6c1n3wWRWzy1tXYdKCoWCbty4QY0aNcpwO7lcTnfv3qWwsLAUXx+i46jIH9vEibG68LNehz9lQGlqqEdFLU3oqQ4H1ppLEqiLX3eKiIig7du30+zZs4mIyMjIiMqUKSMGmJUqVaKKFSuqtE97e3s6deoU/f7772RoaEhWVlZ04sQJatKkCQ0ZMoRat25Nr1+/JqKvF5c2JuZkR10lR70ku0LWVKlSJfL29iYfHx+qUqWKeINgP6fsOLdM6QvdiQin8uXL6+wBUKBAATI2NqZ///2X7OzsyMjIiPLm/a8VZuXKldSiRQvKnz9/lvYPgK5cuULbt28nI4U7fdEz01bRUyma34RMDX/K2z77f4mJiXT+/Hk6duwYHTt2jC5evEhyuZwc/NdTspGFzo6r63Mrvetw0qRJVKVKFXJwcKBPnz7RrFmz6OnTp+Tnl/Y4SLlcTsuXL6c//viDEhMTiejrs9fNzY369OlDgiDQjsRYSjTIo7PP8rNehz9fm+v/83IqoLM8UiQo6OXlIxQUFETGxsY0Z84cev78OYWEhND06dOpTJkydPnyZQoICKCWLVuqvNtJkybRkydPqESJEuIA5LVr11J8fDxNmzaNbGxsxK9vuwM0pcu6kkkl1KZGaVq4cCHZ2NjQ4sWLqXbt2pQvXz5q0KABzZo1i65du0aC8PONJ2G6vw4/XD9FHh4e9Ntvv9Hw4cPpwoULGXYrZ4Wenh4tWLCAli1bRra2ttS8eXPxZ3fv3qXQ0FDq2bOnekUXBDp//jwNGzaMihcvThUrVqSVK1eSnSxaZ/UlIVDVYrp7SLKcIQgCXb16lWbNmkUNGjQgS0tL8vT0pMWLF5OtrS0tXLiQDhw4QEX0YkhXl6JMKiEvxwK62fn/S+86/PjxI/Xq1YucnZ2pUaNGFBMTQ2fPnqXSpUunuR8AVLBgQZoxYwaFhITQ8+fPafbs2WRkZETz58+nadOm0ZdHl4mgm2dSdtRVTpFA23ffXOL+m1iqG3RKZ/tf1syOLh3bS9u3b6fw8HAyMTGhxo0bk6+vLzVq1IjMzMwoKSmJ7t+/n+EEmtxA13V1NKAWORT42r0vCAKFhYWJb8+nTp2iL1++UP78+cnLy4u8vb3J29ubHBwcdNrlwLKHrs+tF8F9qWQBcypcuDBdv36d3r59S0WKFKHWrVuTr68vVatWLdecRwDozJkztH37dtqxYwc9f/6cChYsSK1atSJfX1+qVasWPf7wRaf1FbUugDo186HBgwdTqVKldHYcpjsA6MGDB+I99Pjx4xQVFUUmJiZUs2ZN8R5atmxZOnz4MM2fP58OHz5MNqXKk0GLjMf5auLb+3xul5iYSLt376bt27fTgQMHKD4+nlxcXMjGxoauX79OHxWGZNtrqc6O/yPVlTp+2oCSiKjzygt09tEHrSYolUklVO23/LSu538Tau7fv087duyg7du305UrV8jIyIgaNmxIvr6+1LRp01RjJXMjXdQVQaByhYxoj3/ddDf5vnvmwoULpFAoqGjRouKNsU6dOmRjkx3zX5m2RUVFkc/k3fTRwJog0V6HiEwqoarFLaldwXcUFBREx48fp8KFC1Pjxo1JEATav38/vXr1ir58+aJx2iBtSUhIIGNjY7K1tRUD3urVq5NMJkuxnS6uRQkEcrc1JbdPobRkyRJ68+YNNWzYkPz9/alu3bq5JuhmaXv16hUdP36cjh07RkePHqVnz56RTCajypUri/fJKlWqkKGhIX3+/JnWrl1L8+fPp3v37lGFChUoICCASpQoQd3WXqYkC3sSSHt/77SeibmZXC6nwMBAmjRpElWoUIFq1KhBL1++pL179xIRUefOnWnw4ME048LnbIkffiY/dUD5LCqefOadpEQtTs831JPS0YDaVMTSJM2fP378WAwuL1y4QHZ2dvTs2TOtHV9XdFFXpEimVyv707C+3Wns2LEqPdhjYmLo1KlTYoB548YNIiIqXbq0OP6ydu3aKcawsdxp165d1K9fP0rSNyfLzvNIDu09xL6/Dq9fv07z58+nDRs2kFQqpS5dulDNmjXJ19eXDA0NtXZcTSQlJdHly5epSpUqJJWmH1xr/1oEQZ5MSbvH0dJZgdSwYUPasmULzZs3j8LCwqh06dI0ZMgQ6tSpE5mYpH1fY9krOjqaQkJCxPugMm2Oq6urGEDWqlWL8uT5bwhDZGQkLV68mJYvX04xMTHUqlUr8vf3p/Lly1NgYCDNnDmTnCvWpETv4ZSk0N5jP7NnYm4jl8spNDSUHj16RJs3b6YjR46Qra0tDRgwgHr37k1WVlZElDPxw4/upw4oiYg2X4qkUTtvaG1/M1q5UruKRVXaNjIyknbt2kW9e/cmY2NjrZUhIwCy3Nqg7bqa0qw0PTq6ngIDA8nBwYFWrVpFVapUUWsfb968Ed/Mjx07Rk+ePCGpVEoVK1YUA8yqVavmmlYoRvT27VsaNGgQbd26lZo2bUp//fUXnXohz5br8O3bt/TXX3+JrXCvXr2iggUL5ngLnLrXpbavxdF1itL+hWNo79691K5dO1q4cCFZWVnRqVOnKCgoiPbs2UP58uWjPn360IABAzJNY8a0KyEhgc6ePSve5y5dukSCIJC9vb14n/Py8kq1pCAAOn/+PAUFBdGOHTvIzMyMevXqRQMHDqRixYrRuXPnqEePHvTw4UMaN24cjRw5knaEvcqxZ2JuMWjQIFq0aBF5eHhQQEAA+fr6pjlJNCfjhx/RTx9QEhEtOnGfZh/WJK8UiEhCw+s50QCv9Fe6yHAPGgR66urfvz8lJyeLM83Lli2rcrf7nH9v0sKTT0j5mbPq27qKiIigHj16iBOVAgMDs9wS8ujRI/Gme+zYMXr//j0ZGRlRjRo1xDf38uXLp+pGZLoHgLZs2UKDBg0iALRw4UL6/fffxfNe4+sQIJKodh0mJibSli1bCAB17do168fMQSPWHqetd75ovB9lfQGgzZs306BBg0gikdDChQupXbt2JJFI6NGjR7Rw4UJauXIlffnyhdq2bUtDhgzJMFE7yzqFQkFXr14V72OhoaGUkJBAVlZW4n3M29ubfvvttzR/Pzk5mbZv305BQUF08eJFKlmyJA0ZMoS6du1KZmZmFB8fT//73/8oKCiIPDw8aPXq1SnG8mfntUj0NXVRQkIC5c+fP8PWeV0DQImJidSrVy/q168fVa1aNdPnslhX//+Zs0qT+OFH8UsElERf3zTG/3OT5ALUGhMhIZAiOYm6lDaiyT0yzmuVk5R/xrt379LMmTPp2rVrdPPmTTHBuYODQ4p8mW5ubmRra5viYgJAHTt2pMMP48iybl9SgNSqK5lUQnpSCU1q5pLqLUwul1NQUBCNHTuWChcuTCtXrqTatWtr9JkFQaAbN26IN+WTJ0/S58+fycLCIsUEHycnpxxvofrZvXz5kvr370979uyhdu3a0YIFC6hAgdQzGbN6HcqkElIkJ5FwcRNd3b5Y7JbKDABKSkoSWx9+lPPg/fv35O7uTvkrNaUvpZtmqb7Suxa/bUFu3rw5LV26VByjHBMTQ6tXr6YFCxbQo0ePqGrVquTv70+tWrVSKb8uSxsAunv3rnivOnHiBH369IlMTU2pdu3a4r3K1dU1w4Drw4cPtHz5clq0aBG9fPmSfHx8yN/fnxo2bCj+XkhICPn5+dGLFy8oMDCQ/P390/zbZflalBDJk5OoZMw1OvLXxFTPkJcvX6bK7fjgwQMqUaIEhYaGkpWVVY6cS3K5nPT09OjDhw9qpfg6cOAAtRs9nwo0GkgklWntOvwZ/TIBJdHXMRF/7rpBpx+8//qAyuDEUP68hkN+erM3iK6ePkLXrl2jokV/nJMiKSmJbt++neri/vTpExERWVlZpQgw79y5Q5MnT6bNmzdTtbpN1a6rmg5WNLWla4bjQ+7du0c9e/ak0NBQ6t+/P02fPl1rk5aSkpLo4sWL4k37/PnzlJycTIULF07x1s/dedoDgNauXUsBAQFkaGhIS5cuzTRVVlauw5oOVjSoqhU1rl2FKlSoQAcOHFC7pUMQBJJIJLk+qBQEgRo1akRXrlyha9euEUwsdXIt7ty5k/r370+JiYk0b9486tq1q1g3CoWC9u3bR0FBQRQSEkJFihShgQMHUq9evShfvnxa/8w/oxcvXoiTaI4dO0YvX74kfX19qlKlitiNXalSJdLX1890X7du3aL58+fT33//TQDEiSOurq7iNrGxsTRy5EhaunQp1ahRg1auXEmOjo4Z7jer12JVvSc0oNvvNG7cOHJ0dEzxfHn//j0REVlYWKRqxHB2ds6R/MMKhYIAqB3IRkZGkru7O1WrVo0Wrd5E/9tzU+vX4c/klwoole6/iaUNFyLpxL239PRDyqTLEvqadNTLsQB1qlKUHAqY04cPH6h8+fJkY2NDp06d0tkFERUVRfv376ddu3bR0aNHKTk5mSpXrkytWrWiFi1aaCWYBUCRkZGpgswnT54QEZFMJiN3d3fxBmBVwpXCP5vTmcefKPJDfIpVPNKqK1UIgkBLliyhUaNGUf78+Sk4OJjq1aun8Wf7XlxcHJ0+fVoMMMPCwoiIyMnJSbyhe3p68gMyiyIjI6l379506NAh6tq1K82dO1etZPvfXoeqnluHDx+mBg0a0KRJk+h///tflsodExNDGzdupOXLl9PLly/Jw8OD/Pz8qHHjxuLDPSwsjJYsWUInT56kmJgYIiLKmzcv1a5dm/r370/lypXL0rFVERgYSOPHj6dDhw5R3br/ZUjISn1lJioqigICAujvv/+m+vXr0/Lly1PdZ8LCwmj+/Pm0ceNG0tPTo65du3LaoTR8/PiRTpw4Id5v7t69S0REbm5u4v2mZs2aZGqq2gopgiDQv//++1/aHxsbceKIMk+x0uHDh6lXr1704cMHmj59OvXv31+tF67Mzq0i+YyoVF6B7L48pmc3L1FYWBhdvXpVzB+sTAz+7VfRokW18vL29OlT2r17N+3atYsuXLhA+vr65OPjQy1btqTGjRuL95z379/TypUradmyZfTq1Svy9vamgQMHUr169bLUzZ6UlES1atWi169f09WrV8Xj6OI6/GngF3f1+k3oFyiONXtDEPHiE+ISktPc7sKFC9DX18eQIUOypVwfP37EunXr0Lx5cxgaGoKIULFiRcyYMQMPHjzQ6rGioqJQpEgRODk5Yfbs2ejWrRvc3Nygr68P+jqYEg4ODmjZ5ne4eTZBiUreOH7tHmK/JGl03EePHqFOnTogIvTo0QMfP37UzgdKx7t377B161b07t0bJUqUABFBKpXCw8MDI0eOxOHDhxEfH6/TMvwMFAoFli5dCjMzM9jZ2eHAgQMa7zMuIRkBk+agYOnKGV6HADBu3DhIpVIcO3ZMo2PK5XLs2bMHXl5eICIULlwY7dq1Q8OGDVNcc8OHD8fw4cPh4eEBIoKRkRFatGiB9evX49OnTxqV4XtHjx6FRCLB+PHjM9wuLiEZBZzKY8ikeZnWlyr2798POzs7mJmZYenSpVAoFKm2ef36NSZMmIACBQqAiNCwYUMcOnQIgiBodOwfVXx8PA4fPoyRI0fCw8MDEokERIQSJUqgT58+2Lp1K969e6f2fuPi4rB48WI4OjqCiFChQgWsX78eiYmJqbaNiopC9+7dQUTw9vbGo0ePNPpMgiDg3qOnKOFRG+XqNEejDr1Rwqm0+BzQ19eHm5sbunXrhtmzZ8PJyQnFihXT+r37wYMHmD59unjNGRoaonnz5li3bl2qa+7GjRvw8/ODkZERjIyM0KtXL0RERGhchsGDB0NfXx8XLlxId5u4hGSs3x8CAxtH7DsTpvF1+KP75QPK27dvg4gQGhqa6bYLFy4EEWHbtm3ZULL/xMTEYNOmTWjdujWMjY1BRHB3d8eUKVNw9+5djfYtCAKaNWuGfPny4fHjxyl+lpiYiLCwMKxZswb+/v7w9PSEgYGBeHOxsrKCj48Phg0bhvXr1yMiIgLJyepdUIIgYPny5TA3N4eNjQ327Nmj0edRx5MnT7By5Up06NABBQsWFG9cXl5emDx5Ms6dO6f25/nZPXjwAJ6eniAi9OnTB9HR0Vrb95QpU2BtbZ3pdnK5HD4+PihQoABevHih0TE/fPiA1atXo2bNmmJAIJVKUbVqVRw5ciTV9o8fP8bs2bNRpUoVEBEMDAzQpEkTrFmzBlFRURqV5cWLFyhQoAB8fHwgl8sz3d7a2hpTpkzR6Jjf+vTpE3r37g0igqenZ7ovrgkJCVizZg3c3NxARChdujSWLVuGz58/a60suVFycjLOnTuHyZMnw8vLS7wXFixYEB06dMDKlSvx5MmTLO//6dOnGDFiBCwsLCCVSuHr64vQ0NB0A/Y9e/bAxsYGefLkQXBwsNqBfXJyMiIiIrB+/XoMGzYMPj4+sLKyEu/vBgYG8PT0hL+/P9asWYOwsLBUQe2jR49gYWGBFi1aaPxicefOHUyePFk8r4yNjeHr64vNmzcjJiYmxbYKhQL79+9H3bp1QUSwtbXFlClTshTAp2Xr1q0gIixcuDDTbUNDQ0FEuH37tlaO/SPjgFKNgFIQBLRt2xbm5ua4d+9eNpQutbi4OGzbtg3t2rWDqakpiAiurq6YOHEibt68qfb+Zs6cCSLC3r17Vdq+V69eKFu2LHbv3o0JEyagRYsWsLe3F29CRkZG8PDwgJ+fHxYtWoTQ0NBUN4O0REZGolGjRiAidOjQQWs3BlUJgoAbN24gKCgITZs2hbm5OYgIefLkQbNmzTB//nxERET8sq0xcrkc8+bNg7GxMYoXL46jR49q/RiqBpQA8ObNG9ja2qJWrVpqB/3v3r1DcHAw6tevDz09PUgkEtSsWRPz58/HtWvXMHHiRPEFo0GDBvj333/T/LtHRkYiKCgINWrUgEQigZ6eHho0aIAVK1aoff4mJyejZs2asLW1xZs3b1T6HW0HlEpHjx6Fvb09jI2NMW/evHSDW0EQEBISghYtWkAikcDS0hKjR4/G8+fPtV6mnCAIAiIiIjB//nw0bdoUefLkARHB3NwcTZs2RVBQEG7cuKHRPUEQBJw9exZt27aFTCZD3rx5MWzYsAwD03fv3qF9+/YgIjRq1AjPnj3L9DgxMTEIDQ3FokWL4OfnBw8PD7EVnohgb2+PFi1aYMKECdi9ezfKli2LXr16qfQZ/vnnHxARZs+erfLnVoqIiMCECRNQpkwZEBFMTU3Rrl07bNu2DXFxcam2j42NTdF66+HhgQ0bNqTZeptVd+/ehbm5Odq2bavS35YDyv9wQKlGQAl8vTAdHR1RtmzZHO8ejY+Px65du9CxY0cxAHJ2dsbYsWMRHh6e6cVw6tQpyGQyjBw5UuVj9u7dGx4eHqm+HxUVhZCQEAQFBaXbZe7r64vJkydj3759eP78earyCYKAv//+G/ny5YO1tTW2bt2aYwFccnIyzp49i8DAwBQts4UKFUKHDh2watUqPH36NEfKlt1u376NqlWrQiKRYPDgwYiNjdXJcdQJKAHg9OnTKp+/r1+/xtKlS+Ht7Q2ZTAapVAovLy8sXrwYL1++TLV9QkIC1q5dC3d3d/G6+uuvv9JthXvx4gUWLVoET09PSKVSyGQy+Pj44K+//sLr168zLd+IESMgk8lw+vTpzD/4/9NVQAl8fXAPHjwYEokEVatWzfRh+fDhQ/j7+8Pc3Bx6enro0KFDhl2FudXTp0/FXotChQqlaKkLDAzE2bNntdJrkZSUhI0bN6JSpUogIpQsWRKLFi3K8NoSBAFbtmyBtbU18uXLh3Xr1qV5D33+/Dn27duHyZMnw9fXFw4ODml2WQcFBSEkJCTNlnUPDw/07t1b5c+jPH8ze44KgoDw8HCMHTsWzs7OYoDesWNH7Nq1K91n6tOnTzF8+HCx9bZNmzY4c+aM1p8P8fHxKFu2LBwdHVVqCAE4oPwWB5RqBpQAcP36dRgbG6NHjx46LJl6vnz5gr1796Jr166wsLAQb1KjR4/GlStXUl14WW3hSS+gTEtaXebKsmXUZf7q1Su0bNkSRIRWrVrh1atXatWFLnz+/BmHDx/GiBEjUKFCBbF71MHBQaPxUrlZcnIypk2bBkNDQzg6OqoV7GSFugElAMyaNSvdFvYXL15g4cKFqF27NiQSCWQyGerWrYtly5ap3AooCAJOnjyJli1biq1wo0aNyrBV6PXr1/jrr7/g4+MjBq+enp5YtGhRml30e/bsARFh1qxZqn9w6DagVDp9+jQcHR1haGiIadOmZXqviI6ORlBQEH777TcQEapWrYotW7bk2qEjynHVffr0EQMviUSCChUqYMSIETh8+LBWu/Lfv3+PqVOnwtbWFkQEHx8f7Nu3L80xq99K656YWZe1hYVFpl3W6VE3oFS2sBcuXDjVtSUIAi5fvoxRo0aJdWxhYYGuXbti7969SEhISHOfgiAgNDQUvr6+kMlksLCwwPDhwzUaVpCZHj16wNjYGNevX1f5dzig/A8HlFkIKAFg9erVICKsXr1aNwXTQGJiIg4ePIiePXvC0tISRITixYtj+PDhuHDhApKTk+Ht7Y0CBQqk2TqTEXUCyrQIgoAnT55k2mXes2dP9OjRAxYWFrCwsMDff/+dq7qbP3z4gB07dqB///5i94tEIoG7uzuGDRuGgwcPptll86MIDw9HhQoVIJVKMWLEiGxpjc9KQCkIApo3by6OAY6MjMS8efNQvXp1EBH09PTQsGFDrFy5Eu/fv9eofA8fPkRAQADMzc0hk8nw+++/4/z58xn+zrt377BixQo0aNBA7F6vUaMGgoKCEBkZKY5Ba968udrnd3YElMDXVpsRI0ZAKpWiQoUKCA8Pz/R35HI5du/eLY63LVKkCGbMmKHxOFNNxcXF4eDBgxg2bBjc3d3FF0NHR0f0798fO3bswIcPH7R+3IiICPTu3RtGRkYwNDSEn5+fSkGLIAhYu3ateB/s2bOnSl3WT5480eh+qW5ACaQcA5ycnIzz589j2LBh4v09f/786NmzJw4ePJhhYJuYmIj169eLE3IcHR2xePFinfWMKGX1mc4B5X84oMxiQAlk7W0muyUlJeHIkSPo06cPrK2tQUTImzcviAgLFizI9M34e5oGlOnJrMtc2d08fPjwdLvMc9KzZ8+wZs0adO7cWWx90NfXR61atTBx4kSEhoYiKUmzWfHZITExEePGjYOenh5cXFxw8eLFbDt2VgJKAAgLC4OlpaU4ptjAwABNmzbF2rVrdRLAREdHY/78+WKmgCpVqmDz5s2Z/n2joqKwZs0aNGnSRBxCYWpqCktLS5WCtO9lV0CpdPHiRbi4uEBPTw/jx49XubXr2rVr6NatGwwMDGBiYoJ+/fpl28M3KSkJoaGhmDhxImrWrCneU2xtbdG5c2esWbNGpTGIWfH9xBEbGxtMnjwZb9++Tfd3vu2yHjZsmNjtrm6XtaayElAqFAoEBQWJY8+JCAUKFEDfvn1x9OjRTFup3717h8mTJ8PGxgZEhHr16uHAgQNqP6OyIjw8PMu9jhxQ/ocDSg0Cym/HW2hztquuyOVyzJgxA0QEMzMz8cY6aNAgnDx5UqWZpboKKNPybZd5s2bNUsww19Ysc10QBAG3bt3CwoUL0aJFCzGANzMzQ6NGjTB37lyEh4dny41SHZcuXUKZMmWgp6eHcePGpdsVpSvqBJT37t3DtGnTUKFCBTGIlEql8PHxybZr8fu0Q3Z2dpg+fbpKLVyfPn2Cj48PJBKJeF57eHhg+vTpuH//vkrHz+6AEvg6tlT5wuHq6opLly6p/LvZkXZIoVAgPDwcc+bMQaNGjcT7XN68edGiRQssXLgQt27d0unLqKppfzLrslae182aNVO7y1pTqgaUcrkcISEhGDhwoPgirazzmTNnqvRM0VXaH1VFR0ejZMmSWZ4XwQHlfzig1CCgBL4+2NSZEZaTIiMjkT9/fjRo0ABJSUk4ffo0hgwZgsKFC4vpL/r164djx46lG5hlZ0D5vY8fP6JHjx4gIpQtWxZDhgzR2ixzXZLL5bh48SKmTp0Kb29vsavK2toa7dq1w/LlyzXOH6eJ+Ph4jBw5ElKpFO7u7ggLC8uRcmQWUN6+fRuBgYEoV64ciAgmJiZo06YNtmzZgtjYWCxduhREhE2bNmVjqb8KCwtD9+7dYWBgAGNjY/Tt2zfDB8ymTZtARFi6dCliYmKwefNm+Pr6wsTEBEQENzc3TJ48GXfu3El3HzkRUCpdu3YN7u7ukEqlGDlyJL58+aLy72o77dCjR4+wfPlytGvXTuyFMTQ0hLe3N6ZOnYqLFy+qFNhoKqO0P6rOsh48eDBcXV1BlD25edOTUUCZnJyMY8eOoV+/fmI2BDs7OwwZMgSnT59GcnIyGjRoACsrq3Rbf3Wd9kdVgiCgTZs2GmVu4YDyPxxQahhQAsC2bdtUzlmVU5KSklC1alXY2dmlumgVCgXOnTuHoUOHolixYmLrX69evXDo0KEUXXk5GVAqHTp0CEWLFoWJiYnYba+NWebZ5cuXLzh27BhGjx6NSpUqQSqViuNc/fz8sGnTJpUnjWgqNDQUTk5OMDAwwNSpU3O0W/77gFKZymn8+PFwcXERWz/at2+PHTt2pApABEFAhw4dYGpqmmM39zdv3mSaduj27dswNTVFhw4dUp2DcXFx2L59O37//XexpadMmTKYMGFCqrRVORlQAl/vKVOmTIGBgQGcnJxw5swZtX4/q2mH3rx5g02bNsHPzw/FixcH0dfcoZUqVcLo0aNx7NgxtQJcTaSV9qdPnz5YtWqVyrOsP378CIVCgQULFsDExATFihXD4cOHs6X86fk+oExKSsKhQ4fQq1cvsRXV3t4eQ4cOxblz51L1trx79w52dnaoVq1aintKbGwsFi1apNO0P+pYsGABiDTLLc0B5X84oNRCQAmollU/JwUEBEBPTw9nz57NcDtBEHDp0iWMHDlSnKmZL18+dO/eHfv370fPnj1zPKAEvqZv6t+/P4gI1atXTzPBe1ZnmWe3jx8/Yvfu3Rg0aBBKl/5vVYqyZcsiICAA+/bt03ora1xcHIYMGQKJRIIqVarg1q1bWt1/VigDymvXrmHMmDFwcnISx2N17twZe/bsyTRQiI2NhbOzM1xcXHJ0UlR6aYfevn0LFxcXODs7ZzrJID4+Hrt370anTp3EMWmlSpXC//73P4SFheV4QKl08+ZNVK5cGRKJBEOGDMlSvWeUdigmJgb79u1DQEAAypYtK14fzs7OGDRoEHbv3p3tLXlJSUlYt26d2JqYL18+ODk5IX/+/GrPsr579644iWzAgAE53qMCQJwYuX//fnTv3h358uUD0ddVgEaNGoXLly9n+kJ+9uxZ6OnpYejQoXjy5AmGDRuGvHnz6jTtjzrOnz8PfX19DB48WKP9cED5Hw4otRRQJiYmonLlyihWrJhOZglqYseOHSAizJs3T63fEwRBfLgr3ygNDAyQP39+lR7u2SEkJAQlSpSAkZERZs6cmWlAqOos85zsMn/x4gXWrVuHbt26oUiRIuJs5WrVqmHcuHE4efKkRm/0x44dQ/HixWFsbIy5c+dmS3dgRpQvMbVq1RJba799iVF3LOfNmzdhYmKCLl265PgwlO/TDhkYGEBPT0/tZSMTEhKwb98+dOvWTXwpkslkqFWrlkoPd12Ty+WYM2cOjIyM8Ntvv+H48eNZ2k90dDRmz54tjsczNzcXz4kiRYqgW7duWLduncYrJKlL2WWtXA7w+wmDxYoVU3uWdXJyMmbMmAFDQ0M4ODjg5MmT2fRp0vflyxfs3r0b+fPnF8f2Ojk5iS8x6pxngiBg8ODBYgaM7Ej7o6r379+jaNGiqFy5ssatoxxQ/ocDSi0FlMDXMTSWlpZo3Lhxrplwcf/+feTJkwetW7fWeEWHGzduoHz58jAyMsq0+zE7ff78GX/88QckEgkqVqyIGzduqL2P3NplLggC7t27hyVLlqB169ZiGigTExPUr18fM2fOxNWrV1U636Kjo9GnTx8QEWrXrq3y5A9dSGuYhYmJCYyMjFINs8iKdevWgYgQHByspRJrbsqUKeJLi6pph9KSmJiIf//9F0ZGRuJSrPb29hg2bBjOnz+fo8HlvXv3UKtWLRCpvjSnQqHA1atXMXPmTNSvX18cR2pmZiaOibSxscH06dN1nnYos8TgyuCoZMmSGDFihNhlra7r16/Dw8MDUqkUQ4cOzfH75/fDLIyMjFC+fPksrQ72fdofMzMzGBsbZ+m+rAsKhQKNGjWCpaWlVhan4IDyPxxQajGgBIADBw6AiDBt2jSt7E8T8fHxcHNzg4ODAz59+qSVfSrHUN66dSvDCRI54dy5c3B2doa+vj4mTZqkcVCSG7vMFQoFrly5ghkzZqBevXpiQJE/f374+vpi6dKluHfvXqqHwIEDB2BnZwczMzMsWbIkR154FAqFOBHMzs4u1USwwMDALKUNSk/v3r1haGiIa9euaW2fWXX16lUYGhqid+/eWU479D1ra2sEBgbi6NGj6Nu3rzh7ukiRIvD390doaGiO/Z0XL14MU1NT2NnZ4cCBAyl+rnxJWrp0KXx9fcVuYmNjY9SrVw8zZszAlStXxLLrKu1QZrOs8+bNC1dXVxQtWlScRDdx4sQM0/5kJjExERMnToS+vj6cnZ1x7tw5jT9HVsTGxmLLli0pJoKVK1cOgYGBuHXrVpbSBqWX9icqKgoODg5wd3fPFb1aU6dOBRGlOi+zigPK/3BAqeWAEgD+/PNPSKVShISEaG2fWdGrVy+tP1DTmpTzfQoXIyMjtGzZEhs2bMj2dEpfvnzBn3/+CZlMhnLlyuHKlSta3X9u6zJPSEhASEgIxo4di6pVq0Imk4GIULRoUXTv3h1//fUX2rZtK97gs7u7SS6X48SJExgwYID4oEkvVVVW81Cm58uXL3B3d0eJEiW09kKVFZ8+fUKJEiVSPVA1STsEpJ6U820KF2Vd29jYYODAgQgJCcn2oQ2PHz8WZ/G2bdsWf/31F7p37y4GaDKZDFWrVsXYsWMREhKS6dAGTdIOqbOW9ebNmxEYGJhp2h91Xb58GWXLloVMJsOYMWOyPS1XdHQ0NmzYgJYtW4q9TB4eHpg2bVqqGc7qBJSqpP25du0aDA0N0adPH619nqw4ceIEpFIpxowZo7V9ckD5Hw4odRBQJicnw9PTE4UKFcqxZQP//vtvnXT5ZTbL+9GjR5g1axYqV64sjrlUJpnOzoHzV65cEW/ef/75p87fjHNLl3l0dDT27t0Lf39/sSv52yBuz549Og+ukpOTxWT637aaBQQE4MyZM+m2mmk7oASABw8eIG/evGjVqlWOdAULgoCWLVsib968ePjwYbrbqZt2CMh4lrdCoUBoaCj8/f3F1mB1kkxr6tOnT9izZw8GDRokjodUvuj4+/tj7969WX7ZzCjtUFbWslbelzJK+6OJL1++YPTo0eJL7tWrVzXanzqioqKwdu1aNG3aVBwTWaVKFcyePTvDVGWZBZQKhQL79u2Dj4+Pyml/goODQURYv369Rp8pq169eoWCBQvCy8tLqy9XHFD+hwNKHQSUwNeTt1ChQlo/eVURERGhs0kJ6qQNevr0aYpl8PT19bW2DJ4qEhMTMWnSpBzrXsqpLvO3b9+iXbt2Yqvk4sWL0bNnT7ElVSaToXLlyhgzZgyOHz+ulWD72+U+lV2Y9vb24nKfqpyHuggoAWDnzp1ZmpSmDXPnzgURYdeuXSpt//r160zTDimpOstboVCkuQyen58f/v33X62kivry5QuOHz+OP//8E5UrVxZbyosVK4aePXti8eLFqFevHogI7dq106jbWCkpKQmrV68We0b09fXFISCqzrJOK+3PsGHDtNaSf/bsWZQqVQr6+voIDAzMlrRc79+/x8qVK9GwYUPo6+unWu5TFekFlMq0PyVLllQ77Y8gCOjSpQtMTExw8+ZNtT+XJnTZyMMB5X84oNRRQAnopnk9M7GxsShVqpTO0qZkNQ/l8+fPsXDhQtSuXRsSiQQymQx169bFsmXLdJ5z8caNG6hYsSIkEgn++OOPHB0Ar8suc0EQsGnTJlhZWSF//vzYuHFjqkDk4cOHWLZsGdq2bSuOFzMyMoKPjw+mTZumVhLohIQE7N27F127dhUDZQcHB4wePRpXrlxR+2VGVwElAPzxxx8qpc3SpjNnzohpU9SVVtqh75N/ZyVtkCAIuHz5MkaNGiW23OXLlw/dunXDvn37VO6GVSbrnzZtGnx8fMQuVCsrK7Rt2xbLli3DgwcPUpwDgiBg48aNyJ8/P6ysrLBp0yaVz5HMuqwLFy6MEiVKwMDAADKZDM2bN89wwlNSUhI2btyISpUqgYhQsmRJLFq0SGvjvz9//oyAgACNJgqq482bN1i2bBnq1q0LmUwGiUSC2rVrY9GiRVmaEf99QPlt2h+ZTJbltD9xcXEqp83SJl0OQ+OA8j8cUOowoASAadOmgYiwf/9+nez/W4IgoH379jAzM9PZya2NxOavXr3C0qVL4e3tDalUCqlUCi8vLyxevBgvX77UUklTSk5OxqxZs2BkZIQSJUrk+PjW72naZf7y5Us0b95cHK+mSpCuUCgQFhaGOXPmoGHDhuJa2BYWFmjZsiUWLVqE27dvpzhOfHw8du3ahY4dO8Lc3BxEX3Mjjh07FuHh4Rq1iOsyoExKSkK1atXSTOyvC8rEztWrV9eoVer7tEOWlpYYNWoUnj17pnEeSkEQEB4ejrFjx6JUqVIg+przs1OnTti9e3eKZegEQcDt27exaNEitGzZUnyBMDU1RcOGDTF79myEhYWpNAnozZs3aNOmDYgIzZs3T3HNa9JlDXwNWBYsWCDm0K1atSq2bNkitvy/e/cOU6ZMEbvhfXx8cOjQIa1OXjpx4oSYymzWrFk6G17w8uVLLF68GF5eXpBKpZDJZPD29sbSpUvx+vVrjfZdvXp1DBgwAGfPnhUXC7CxscGYMWNUbuVMz+3bt2FmZoaOHTtmyzCU/fv363Si7NmzZ2FsbJzhqla/Cg4odRxQKhQKNGnSRGspCjKyZMkSEOl26Tltr5Tz9u1bBAcHo379+tDT04NEIkHNmjUxf/78dJft0sTdu3dRo0YNEBH69++fK5IIp0eVLnNvb280aNAAJiYmyJ8/P7Zu3arR8U6fPo0JEyagZs2a0NPTE8dH1a5dG5UqVRK7FF1dXTFx4kStdl3pMqAEgGfPnsHKygr169fX6exnhUKB+vXrZ7j0XFY8fPgQAQEBMDc3h0wmg6GhIfr27au1/UdERGDChAkoU6aMmLmhcuXKqF27thiA6enpoWbNmpgwYQJOnz6t0USVLVu2IH/+/DAxMUGDBg3g7e2dYpa1qonB06Ic4+fp6QkiQqFChVCpUiUYGhrC0NAQfn5+aS6GoImYmBj069cPRIQaNWpoff/A13N4/vz5qFmzJiQSCfT09NCgQQMEBwdrZRhBdlEuPfrXX3/p9DjKVH5NmjTJNan8fmYcUOo4oASADx8+oFixYlpJopqeS5cuwcDAAP3799fJ/pV0ufTihw8fsHr1ajRu3FhsnatatSrmzJmj1dnJCoUCCxcuhKmpKYoWLYpDhw5pbd+69m2Xub+/vzjpRduzzGNiYrB69WpUr15dDCyVX8WLF8eAAQOwc+dOreYF1HVACXxdtlMikSAwMFBnx5g0aRIkEonOls9Tph1SJvzOatqh70VFRWHnzp0YMGCAuKSh8ktPTw/Vq1fHmjVrstRVmVmXtXLSkL+/v8qJwTMjCAIuXryIKlWqpGjh7Nmzp9ZbqZXLwZqammLz5s1abXn7/PkzXr9+jbNnz6J58+YwMDBAkyZNsGbNGp3n5dSl/v37w8DAQOuZOJRy82IjPysOKLMhoASACxcuaGWZp7RERUXB3t4eHh4eOk9FkV1reX/8+BHr1q1D8+bNxQdPxYoVMWPGDDx48EArx3j06BHq1KkDIkKPHj2yffm2rFIoFFi6dCnMzMxgZ2eH/fv3a2WW+adPnzKs83fv3mHr1q3o3bu3mENRKpXCw8MDI0eOxJEjR1J0k6orOwJKAJg+fTpcXV11skzq0aNHIZFIMH78eK3v+3vW1tbo1KlTltMOxcfH4/Dhwxg5cqSYZJvo6/J6vXv3xpYtW/D27Vvcv38f06dPR8WKFcXj/PXXX7hw4UKqcdppdVk7OTnBy8sLvXr1QkBAAOrXr5+qy3rfvn0oXLgwzMzMsHTpUq20JinHAu/fvx9bt25FZGQkli1bhrt372qtterjx4/o0aMHiAje3t5aG7Lz8eNHJCYmQhAE8XMo/6vJNZabJCQkwMPDA8WLF9fJvTe3L4f8M/rlA8q4uDgcOXIkW4KJhQsXgog06pb8niAIaNasGfLly4fHjx9rbb/puXXrVrZfoDExMdi0aRNat24tdrm6u7tjypQpGncrCYKA5cuXw9zcHDY2NtizZ4+WSq0bDx48EAOI3r17Z5gCSJUu89q1a6NBgwZwc3MTWyKVrcKZnU9PnjzBypUr0b59e3FWsqGhIby8vDB58mScO3dOrfFjt27dwu7du1XePqu+nyiiLa9fv0aBAgXg4+OTLZkddu/eLa7B/vHjR1y8eBHbtm3D9u3bcfny5VT3tOTkZJw7dw6TJ0+Gl5eX+NJQoEABtG/fHitWrMj0b/727VsoFArxC/h6fW7evBm+vr4puqx/++03BAcHiy3kgiBkWN+fPn1Cr169QETw8vLS2ovj98fU1t98z549sLGxQZ48eRAcHKzxfp8+fYpbt25BoVDoPK1TbvHo0SNYWFigRYsWWr0Wt27dCiLCwoULtbZPlrlfPqDMToIgoG3btjA3N9fa+JqZM2eCiLB3716t7C+3i4uLw7Zt29CuXTtxEok2xvNFRkaiUaNGICJ06NAhWyZuqEMulyMoKAgmJiawt7fH0aNHs7QfQRBw9epVDBgwACVKlIBEIknR7WhoaJilLnPl0pxBQUFo2rSpOGEnT548GDlyJJKSkjINKBQKRY6sK66tB5lCocDhw4d1nrVASS6Xp2ppEwRBrEdlnScmJmLkyJHIkycPiL6uj92kSRMEBQXhxo0bKicGv3HjBhQKRZrbJycnQy6XY+/evVi5ciXevXuX5Xo9cuQI7O3tYWxsjHnz5uX4WvPfe/fuHdq3bw8iQqNGjTQaJ/v69Wv8888/4otBdqQVym3++ecfEBFmz56tlf3dvXsX5ubmaNu2bY6vcf+r4YAym8XExMDR0RFly5bVysoLMpkMI0eO1FLpfixpzTh2dnbO8oxjQRDw999/I1++fLC2tsbWrVtzxQ3p9u3bqFq1KiQSCQYPHpylMWyvX78WZ9bLZLJUM+u1nZg9OTkZZ8+exaxZs/Dly5dfpsUlN0pOTsbnz5/Rvn17HD9+PMO/RUazrK9fv57p31F5TmjapRwbG4tBgwaJLebfZ63I7OVEG9Jq2dyyZQusra2RL18+rFu3TqMyfPsZdP1Znjx5kquvwREjRkAmkyE8PFyj/SQlJcHNzQ2Ojo65esLlz4oDyhwQERGBbdu2abQPZcvDtGnTcvWNIruklROxZMmSWcqJ+OrVK7Rs2RJEhFatWuXYakcKhQLTpk2DoaEhHB0dcfr0abV+/8WLFxrl/syNa5mzrBEEAd26dYOlpSVGjx6NZ8+eZbqW9bezrP/9998cKfepU6dQsmRJGBoaYtq0aXj16hVu3LiRredZaGgonj17livuCeoQBAGhoaHw9fWFVCrN9qUe1ZGcnIwlS5ZALpdrHKQfP3482xOns684oMwh2hgUzmkQ0vbtqi2WlpbizGR1Vm0RBAFbt26FtbU1ChcujNjY2GxvrUxKSkLevHkxYsQIlQfif786kZ6enlZXJ1I3MfurV69yRSvvr04QBHH8rXL1FOUkHOWqRsq1rLU1y1qVMqkiPj4e3bt3h0QiQZMmTbK1DAqFAu/evYOlpSVMTU2xevVqrR5fFxITE7F+/Xp4eHiAiODo6IglS5b8MtchPxdzDgeU7KeWlJQkrittbW0Noq/rCWe2rrTSu3fvsH///hwbx6XKxISM1k/PrrQi6XWZr1u3jlstc4Hk5GSsW7cO+vr6cHV1RaVKlcTWyIoVK2ol7VBWbd68Oc3JQAqFAvv370fdunXFl8K3b9+qdS2q06Wc3jbJycnYsWMHDAwMYGJign79+uXKVVHevXuHyZMnw8bGRlx29cCBAxxgsWzDASX7Zcjlcpw4cQIDBgxAoUKFxKTdgwYNwsmTJ7MlaMzKwzAt9+7dw7Rp08R1jI2MjNCyZUts2LAB0dHR2iiqxhITExEVFfXDPdB+xpYchUKBqKioFOO25XI59uzZk+W0Q9oql3IlEw8PD0yfPh3h4eFYvHgxHB0dQUSoUKEC1q9fr1Z3qPKcU3V7VQLPqKgoTJgwQcz92rBhQxw4cADv37/X+b0jo3JFRETAz88PRkZGMDIyQu/evREREaHT8jCWFg4o2S9JoVDg9OnTGDJkCAoXLgwiQsGCBdGvXz8cO3ZMq61qgYGBGDhwoMb7uX37NgIDA1GuXDlxJZM2bdpgy5Yt2boubm7i5+eH4OBgPHr0KKeLkmWPHj1CcHAw/Pz8cqwMYWFh6N69OwwMDGBsbIy+ffvqZKWXtAiCgPv376Njx44pJoK5uLikuR59Zr5NuzNy5EiMGzdOq62vcXFxGDFiBPLnzw8HBweVXpiUAWd4eLjW0iEpdenSBba2tpg6dapWslO8ePEC48aNQ4cOHTB06NBc2Rqbm3B9/YcDylzk8+fP4v8rb4C/YhqJ7KZQKHDu3DkMHToUxYoVAxGhSZMm+PLli1Zyy0kkEkgkEjHHorrB6tatW+Hi4gIigpmZGdq3b48dO3akOF9+VfXq1RPHAhYvXhx+fn7YtGmT2ql7lA/8LVu24Pz58zptpXzz5g02bdoEPz8/cUUaqVSKevXq6eyYqnr9+jUmTpyI9u3bIzo6Ot00QdqmUCjw5csX9OnTB82aNUOzZs1gZmYmdslHR0dnWA5BEBAcHIwTJ06I3wsNDUXNmjWxcOFCfPnyReMyKtdVVw4VKFasGP79999MA0q5XC6eXy1atICfn5/WWoEVCgU+ffqk0XPC2NhYXLbx5s2byJs3LxwcHNCmTRuUKlUKJiYmGs++zqrc+EzMzfWV0zig/EZYWBikUmmOHX/58uXo1KlTiu8pUx8sX75cZ8s2ZlVO15cuCIKA8PBwjWcbKh0+fBgVK1bEoEGDYGdnJz7YVO0iUygU2LlzJzp37ow9e/Zo5cGYW+zfvx89e/bE8OHDU73VR0VFwcvLK9N9tG7dGgMHDkRAQAA6dOgAZ2dnsYWrbNmyWLx4cYa/r8zbqPxb16xZE2PHjk1Rz8qAoVmzZti2bZvGs1CVSeCdnZ3RoUMHBAQEYODAgWjdunW6v6eNulK3nOp8TmUdnT17FtWrV8edO3eydMxvffnyBXv27MHhw4czvV4EQcDKlSuhr6+PXr16QS6Xo3379hgyZIjYev19QvusXkvBwcG4fPlypvXz/v37FJPpwsLCULt2bezYsSPFdsrPNn78+GxrFf6WRCIRX8CaN2+Opk2bii+9CoUCv//+u9YnQ6kqNz4Tc3N95TQOKL8RFhYGiUSSY8d//PgxrK2tMWXKFABf38QqV66Mhg0bwtTUFOvXr8+xsqUlp+vrR3DhwgW0bNkSZ8+eRalSpdClSxe19/EzjunbsGEDZDIZGjdujBo1asDIyCjF+f369WuVXla6dOmSapZ52bJlUbt2bVSuXFmtWbmPHz9GrVq1sGvXrlQ/i4yMhEQiSbFEqzKIUjcdS+/evVG2bNkUa1nb29une25oq6504dvWty1btqB58+aoW7cuXr9+LW6TnefvtWvXULduXeTNmxcVKlQQ08coFIoULVvbt2+HlZVVinKqQp3P8vfff8PKygrt27cXW3579eoldnkrg6H4+Hjcvn0bEokER48eTbHcYnb4NkAqUqQITp06leLnV69ehY2NTbaV51u58ZmYm+srp+nRL6RVq1YZ/jw6OpokEkk2lSY1e3t7Wrp0KfXp04dGjBhBDx8+pOfPn9Ply5dp4cKF1Lp162wtT26vrx/B3bt3KSEhgapWrUpDhw6lYcOG0b///ksvXrwgDw8PKleuXKb7+BnreNasWTR37lwaPHgwERFt3bqVevToQQkJCdSzZ0+V97N27VoiIvr48SNdv36dwsLCxK+bN2+Sh4cHAUizDp8/f04rV64kV1dXatWqFd2/f5/y589PZcuWJSKipKQkMjAwoFu3blGZMmXIyMiIgoODKSkpiby8vEgqldKDBw9o/vz5dOrUKZLJZNS6dWvq0aMH2djYpFvmpKQkKl++PPXo0YPc3NyoXLlyZGFhofO60qbPnz+TTCYjIyMj8Xv79++nf/75h3777TcKDw+nevXqERHRwYMHaePGjdStWzfy8fHRWZkUCgW5ubnR5MmT6ffff6c7d+7QhAkTaOvWrSSVSkkqldLHjx/JycmJkpOTqV+/flSwYEFSKBQkk8lUOoY612Lnzp2pWLFitGLFCipZsiRJpVLq2rUrlShRgoiIDAwMiIho7ty5NHbsWCpSpAiVKlWKJBIJyWQyksvltHLlSmrbti3ly5dP/QpRkUQiET+XVCqlvHnzpvi5hYUFffz4UWfHz0hueyYS5e76ynE5HdFmJ2VOvm7duqX51axZsxztwlU2mz979gzTp09HkSJF4Ovri2rVqqFGjRrZXp7cXl+5xY0bNxAcHCz++/Dhw+L/Hzp0CB06dADwtZWkXr16kEgkcHFxwatXr364GdDaYmpqmmoizfHjx2FmZoalS5dqpdUtMTExw/p99uwZ+vbtiyJFiiBv3rywsrJCuXLl0lxPvH379nByckKzZs1QsGBBzJgxA9HR0WjVqhWKFy+Offv2YeHChahZsya6d++e7jGz0lqXHXWlrsOHD6NAgQLo2LEjwsLCAABjxoyBm5sbOnXqBIlEgsaNGwP4ukb34MGDYWJiguLFi2PJkiVaL8+3f+c2bdpg8ODBOHz4MBo2bAgLC4sUC0k4OjrC2NgYjRo1ElsJdX0d/u9//0PJkiVhbW0NR0dHzJo1S/zZ+/fvYWBggFKlSkEikaBDhw74+PEjXr16hSZNmkAikaBZs2a4du2aTsomkUhgYWGBfPnyiam+vnX48GHY29vr5NiZyW3PRCB311dO+6UCSldXV6xYsSLdn1+7di3HAiTlg0Yul6NXr14oWrQohg0bhtu3b+Pz588wMDAQb8TZNVA+N9dXbjJs2DAULVoUy5cvh7OzM/Llyyfmf1y6dCl69+4NAOjWrRv09fVRoEABMej4GbuzVWFjY4Nz586l+n5ISAjMzMwwZsyYbDu3kpOTcf/+fZQuXRply5aFra0tLC0t4ezsLI5pc3R0xOTJk8XfkcvluHXrFkqXLo3ly5eL39+2bRtsbW3xzz//aK18uamuvnXq1Cm0atUKTk5OuHTpEkqUKIFx48YB+Fo/9+/fT7H958+fsWzZMhQrVgxWVlYIDAzUepmmTJmCBg0a4Pjx4+L3Zs6cKXaZbtmyBVKpFOvXr4eXlxdsbW3x9OlTJCUl4f3797h48aLWJsx8e0+vV68e5s6di+fPn2PFihWwsbHB//73PwBfs0DY2dkhISEBt27dwvTp01OMDYyIiECnTp1gYmICDw8PHD16VCvlU1qzZk2Kr+/PtUmTJiEgIECrx1RFZs9EPT09LFy4MMW22SG31ldu8EsFlN26dUP//v3T/fmtW7dy9M3iw4cPaNy4McqXL4+lS5fixYsX4s+ePn0K4OsYkj179og3I13K7fWV0769iRUrVgwSiQSdO3dOsU1QUBAqVqwIa2trVKhQASdPnsSKFStgamqK/fv3Z3eRc43mzZuLwcf3Tpw4AVNT02wJkpR/w3v37qFmzZo4cuQIkpOTcenSJcyZMwcfPnxAZGQkZDJZihnEwNexk506dcL48ePF761Zswbu7u5ii5g2HnS5pa4yMmvWLJQuXRpHjhxJ8+fftgBOmzYNZmZm6NmzJwDtBQNJSUkYMmQIZs6cKabR+nbf7969Q8GCBTFo0CDxe8eOHQMArFq1CiVLlkS5cuVgY2ODOXPmaFwe5WfeuHEj6tWrl2L8rVwuR2xsLJKSkmBnZ5fm/VyhUKSotxcvXkAikaBYsWK4ceOGxuX7EWT0TPw2k8Ov2tOT2/xSAWVCQkKuTrVy+fJllCtXDmvWrEkxO/DbGZdfvnzBjh074OLigpEjR+q0PLm9vnKL48ePw93dHVZWVqlSlBw6dAh58+bFjBkzxIdcZGQkWrRokW6Q8CsICQnB1KlT0/358ePH0a1bN52XQ9mltnr1arRs2TLNNYDXr1+PfPnyialClF6+fAl/f38YGhrC2toadevWRbVq1TBmzBh8/PhRa2XMLXWVkYoVK6JPnz5iHX0/oxr4ej9ZsWIFJBIJ5s6dK9aRtluXlIn9v09W3qVLFzg4OKSaiPPq1SvUqlULHTp0wJ07d7Bz506UKFECf/zxB5KSkjQuX//+/dG/f/8UdaPc58aNG2FiYpJubkrl5JywsDC0bdsWRYsWxcWLFzUqT3q8vLzSPG+jo6O1nkVAVek9E4GvAfbhw4fRo0cPtGnTBpMnTxZfELJDbqyvnPZLBZS53blz52BpaYl79+4BSD+1jFwux+XLl2FmZoa9e/dmZxFZBkaMGAFXV1ccPHgwxfefP3+eattPnz5lV7FYBpQP9s6dO6N79+4pgkbl9de1a1c0aNAAwH8B6MWLF9GgQQN4enrizJkz2Lp1Kzw9PdGvX79s/gQ5R1l3p06dQrFixbB58+YMt586dSqKFy+erXWkbLkKDQ2FRCLBv//+CyBlEBsfH4+qVatiz5494vdWr16NcuXKaW3Vqe9fRpTlqlKlCrp27Zrh737+/BmVK1dGhQoVxPLrwrezl7/15s0b6Onp6ey4Gfn+mah08eJFdO3aFW5ubqhYsSKCgoLQunVrFCtWLM0sDbqQG+srp/2SAaVUKk3zRHj//n2Odx21b98eRYoUSfE95c1v165dKdZmnjhxIlq0aKHzXFy5ub5y0vfpPe7cuQM3Nzd06NABDx8+THP7X3XMZHq0fW4JgoDnz5+n6p7OzJs3b3Dnzp00W9aqVauWaijDqFGj4OXlleLvvG/fPpQoUQKHDh1Ks1yfPn3C5MmTsW/fPjx//lztcyG3XoeXLl2Cm5tbuuNG5XI5goODIZFIMGPGDHGMYnZ2Uw4fPhyVK1dONVHr7NmzGDNmDBo0aCBOIgKARYsWwdHREVeuXNFZmWJiYmBjY5PmJCXlfSUiIgIdO3ZEwYIFddYyGR4ejvDwcEgkEpw4cUL8d3h4OK5evYqpU6eiWLFiOjm2Ktq3b49ixYqJL3Pnz59H7dq1IZFIYGZmhvHjx4vX4fz585EnTx6100GpI7fXV076JQPK9N4sXrx4ASMjoxwoUUoHDhyAIAi4cOFCiu/36tULlSpVEv/drVu3bEmgmtvrK6edOnUK+fLlQ1BQEP755x8UKVIEc+bMgVwux8OHD1PMAGcpaXpu3b59G+vXr8ewYcPg4+MjrmKizRmga9euReHChdGyZUscOHAAwNeXOScnpxSJqGNiYmBnZyf+vb8PTkNDQ5EnTx4x96SVlRV8fHwwbNgwrF+/PtMl23LrdRgTE4P27dsjT5486NKlS6pu4pkzZ6JkyZLo27dvjpVx69atsLKywtatW8XvLViwAGXLlkW9evWwYMECeHh4wMzMDO3atYOTkxPat2+v0zLFx8dj8ODBKFy4MP7+++9UAXZiYiKqVauG8uXL63S8tUQigVQqhVQqFVf1+vbLxMQEK1eu1NnxVfFt63GTJk1gbGyMVatWYcOGDfjf//6HAgUKiK3A3bt3x4IFC3RWlh+hvnLKL5WHcsGCBUT0NY/UihUryMzMTPyZQqGgU6dOUalSpXKqeKKGDRvSzp076cKFC1SyZEkxB9mkSZOoXLly1LRpU9LT06PXr1+Tp6cnASAi7ecr/FHqSxdiY2MpMjKSnJ2dSSqVprtdcHAw9e3bl/7880/y8/MjU1NTCgkJoWXLltE///xDZ86cod9//538/Pw0Kg/SyaX4o9LWuVWzZk16//492dvbU+nSpcnb25tiY2PFa0IbunTpQg4ODrRx40Y6evQoNWzYkNq2bUtbt26lzZs3i7kgZ82aRTExMWL+xW//XhKJhLZv304xMTFUokQJcnJyInNzc4qNjaXt27fT7NmzycrKit69e5fq+Ln9OjQ3N6eNGzfS2bNnae/evaSvry+WbePGjfS///2Pxo4dS/369SMiIkEQMrymvieXy8U8klnVpk0b+vDhA/Xv35/09fXJx8eH9u/fTzVq1KCZM2eSqakp9enThzp16kT58+enHTt2UMGCBVOVVxAEksvlYg5JTRgbG9P8+fOpZMmSNG/ePCpcuDDVqVOHiIgePHhAEyZMoLt379KhQ4eoQoUKGh8vPY8fPyYA9Ntvv9HFixfJ2tpa/JmBgQEVKFBA5TydutKsWTMiItq4cSMdO3aMzp8/L+aLJSK6fPkyBQcH059//kl9+/alQoUK6awsP0J95ZgcDWezmb29Pezt7SGRSFCkSBHx3/b29nB0dES9evVw/vz5nC4mgK9jR2xsbHD69OkU32/dujX69++PsWPHYvTo0VpLcZGWH6m+tOHTp09Yt24dmjdvDkNDQ7i5uWX6OxcvXsT169cB/NeFl5iYiK1bt2L48OFaqR9BEPD+/Xu0adMGM2bMSHcA/49EW+fW4sWLMWTIEHh4eIhrepcoUQJ9+/bV6WojgiBg27ZtKFu2LExNTeHq6gp3d3fMnj073d959+4dtmzZgt69e6NEiRLiGt4eHh4YMmRIustEZvd1GBcXhxcvXmhcfytWrICxsTH8/PxU2j45ORnv379HVFQUHjx4gBkzZqBixYqoU6eORuX4VmxsrDi5w9PTM9WyfuPHjxfXVP9+SIJCocDLly9hbW2NFi1aYOPGjTpJ4RYbGwsHBwd4eHiI4wEzW8dc2549e5YrZ06vWrUKVapUQVxcHJKSksQVkCpXrixeezkxrCi31ld2+6UCSiVPT09xLOLp06dz7frIf/zxB5ydnfHixQskJycjNjYWNWrUwNq1a1Nsp+sT+Uepr6z48OEDVq9ejcaNG0NfXx9EhKpVq2LOnDl4/Pix2vvTxd9CLpdj586daN26NYyNjUFEcHd3x5QpU3Jk7V9t0vTcsrKyQsGCBdG+fXusWLEiS38zTb1//x7Hjx9PlXcxM48fP8aKFSvQvn17FChQAFZWVhlur+vr8OnTpxgxYgQsLCxgbGyMbdu2aXw+nz17Fu/evQOQ8fr1CoUC+/fvh6WlpfhiYGhoCF9fX2zevDnDceLqBhDKzzR58mTUrFlTfEGLiYnB0KFD4eLiku4+X79+jTlz5qBKlSogolQBqTbExcVhyJAhKo2ZTEpKwpYtW7Bs2TKtZuQwNzdPcxx4Tlu1ahVKlCiR4nw4ePAgjIyMUiUYz065tb6y2y8ZUH4rt58IDRs2RJ06ddCoUSPUrVsX+vr6uHTpkvjz7H4by+31pYp3794hODgY9evXh56eHiQSCWrWrIn58+fj2bNn2VoWdf9+cXFx2LZtG9q1awdTU1MQEVxdXTFx4sQ0U978SLJybt26deunmOgkCAJu3bql8vbaug4FQcDZs2fRtm1byGQy5M2bF8OGDcOTJ0803reqx09MTESdOnVARDAxMUGZMmVgYWEBIkKDBg3w77//Zvg3/n4ylaoSEhLQtm1b5M+fH/369UPVqlWRJ08ecZxlWsF0bGwsFi1ahJIlS4qt4brsJVLFwIEDIZFIYGlpidGjR6eZVUJdZmZmufY+X716dTRo0AAjR45Ev379IJFIMGTIkBwtU26ur+z0yweUOX0iZHYj/Pz5M1auXImOHTuiefPmOZ7QNqfrK6tev36NpUuXwtvbGzKZDFKpFF5eXli8eDFevnyZ08VLU2azwuPj47Fr1y507NgR5ubmICI4Oztj7NixCA8Pz5FASznLet++fZg8eTJOnjwpzs7MzI96buUEdesqOTkZJ0+eFGeZP3r0COvXr0fFihVBRChZsiQWLVok5krNLnK5HBMnTkSnTp2we/dusTs6ISEBa9euhbu7u3heKydEZSQr5/w///yDnj17YuTIkdiwYUOaZUxMTMTYsWORN29eyGQytG3bFmfPnk2V6zKnPHz4EP7+/jA3N4eenh46dOiQalKnOnLztRgTE4MRI0agcePGqFq1KjZt2qS19E5ZlZvrKztJAC2OXv8BmZubU3h4OP3222/ZelxoMMlC3UHt2pRT9ZUVL1++pJ07d9L27dvp1KlTJJVKqU6dOuTr60stWrSgAgUKZPj7crmcZs+eTV26dCFbW9tsKvVXgiBQUFAQnTlzhhYvXpzpIPPExEQ6cuQIbd++nfbs2UOfPn2ikiVLkq+vL/n6+pK7u7vWJ/XI5XK6e/cuhYWFpfh6//49ERFZWFjQ5s2bycfHR6VB6j/SuZXT1K0rhUJBR48epXbt2lF0dLT4fUtLS/L09KQWLVpQ+fLlycnJifT0sm+upiAIlJycTIaGhmn+HACdPn2apk+fTgcPHqS///6b2rdvn24ZtXVv/P7+3KJFCzp06BANHDiQBg0aREWLFtX4GLoQExNDq1evpgULFtCjR4+oWrVq5O/vTy1btszw7/r333+n+HefPn0oMDAwxT2yS5cuOiv3j4brK22/fEC5ceNGat68OZmammbbMQVBIEEQiIjUvnl/e6OTy+UUHx9PefLk0XoZ05MT9aWOZ8+e0Y4dO2j79u105swZ0tPTo7p165Kvry81b96c8ufPr9J+rl+/Tj169KBr167RiRMnqGbNmtk6yxoA7dq1i/r27UtyuZzmz59PnTp1UqkMSUlJdPz4cdq+fTvt2rWLoqKiqHjx4mJwWbFiRbU/S2xsLF2/fj1F4Hjjxg1KTEwkIiJ7e3tyc3NL8VW0aFG1jpPbz63cRN26AkAHDx6kVq1aEQCqXbs2OTg40KtXrygsLIyePHlCRERGRkbk6uqa4u/o6upK5ubmOvw0GZd73bp15O/vTxKJhOrWrUuLFy8mCwuLbJlJK5fL6dChQxQUFETHjx8nd3d3WrVqVYoZxrmRQqGgffv2UVBQEIWEhFCRIkXo0aNH6T5vvLy8Uvz79OnT5OHhQcbGxkT0NcPA8ePHdVrmL1++kJ6enpglIDPKZ+G3z0SFQkFSqZQA6LTRJTfUV66UA62iv7xx48ahYsWKGg+qv3DhAqytrcVZxr+qR48eYdasWahcuTKICAYGBmjatCnWrl2bIhG8KhITEzF+/Hjo6enBxcVFZ8mEVfXu3Tt06NABRIRGjRqpPcYzKSkJR44cQZ8+fWBtbQ0iQpEiRRAQEIAzZ86kGif2fZe1r68vHBwcxNyJ+vr6cHNzQ7du3RAUFISQkJAMlxlUtbs7J+R0N2V2a9iwISZPnpxq1RYA+PjxI0JCQhAUFIRu3brBzc1NnKQmkUhQuXJllf+W2qrXyMhINGzYEESEjh07ipN7sms5WOUMYuU1cuHCBbi4uEBPTw/jx4/X2oISuj4Pr127hm7duqn1vMnuLtzr16+jaNGimeZizUxSUhJ8fHwwfvx47RRMRdzl/RUHlNns0KFDkEgkCAwM1Hhf8fHxKFu2LBwdHXN8DEl2u3//PqZNm4YKFSqAiGBkZISWLVtiw4YNWa6LS5cuwdXVFXp6ehg3bhwSEhK0XOqs++eff2Bra4s8efJg+fLlWXoIyeVynDhxAgMGDEChQoVARChQoADq1auHdu3awdvbW0wMTkSwsLCAp6cn/P39sWbNGoSFhWX6EFUoFAgPD8fcuXPRuHFjmJmZYc+ePTpN4ZNVv0pAKZfLsWfPHpiZmaFx48aYO3cuwsPDM53BnZiYiLCwMKxZswb+/v7YsWNHhkFlUlISgK+z3jVZFUoQBCxbtgzm5uawtbVNdwWenPj7JSQkYOzYsdDT04Orq2uKCZLqUNZPYmKieL/S9TWiTn1lZ4AUHR0NR0dHlCtXLtV63VkxadIkSCSSNFes0hUOKL/igDIbPXv2DFZWVmjQoIHW0svcu3cP5ubmaNu27U//gLx9+zYCAwNRrlw5cUZomzZtsGXLFo0mE3z58gUjR46EVCqFu7s7wsLCtFhq7fn48SN69uwJIoK3tzcePXqk8u/GxMQgNDQUixYtgp+fHypUqCC2QCm/DA0N4eHhgUmTJuHBgwcqn0+PHj1CcHAw2rVrJ7aCGhoawtvbG1OnTsXFixdzXY62TZs2wd7eXq06zIwySMhN12FSUhLkcjkuXryIqVOnwtvbG4aGhiAiWFtb4/fff0dwcLDK9fD951MoFOKkleXLl4trK48ePRrXrl2DXC5Xqz4ePnwozvju2bNnhq3fOenatWtwd3eHVCrFyJEjNeptio2NxenTp8UsDcrAPCdlV4AkCALatm0Lc3PzVOt1Z5VCoUD9+vVhZWWVbVk7OKD86pcPKJ88eYJatWrpvNs4KSkJ1apVg52dndh1oy3btm0DEWHhwoVa3W9aZs2ahd69e+v8OMDXm82NGzcwfvx4uLi4gIhgZmaG9u3bY8eOHVrp+jpz5gycnJxgYGCAqVOn5oqbeWYOHTqEokWLwsTEBAsWLEgRrGWly/rDhw84d+4chg4dimLFionLAvbq1QuHDh1KVSdv3rzBpk2b4Ofnh+LFi4sJuitVqoTRo0fj6NGjWWppCA4Ohqenp8b1k5nbt2/D1NQUHTp00GrwJwgCrl69in379qk91CIrPD09sXz5coSFhWH48OFwd3dH9erVMWfOHLx48SLd34uPj8fRo0cxevRoVKpUScz7WLx4cfj5+WHTpk2plnhMSkrCoUOHEBAQgODgYERHRyMmJgYvX75EZGQkoqKi0uwyNzc3x6BBg3D9+nUxGXVkZCRevXqVKjBdsGABTExMUKxYMRw+fFgrdZScnJwiCFa2sGrjBScpKQlTpkyBgYEBnJyccObMGY33GR8fj8ePHyM5OTnNFsvselmZOnVqtgTzCxcuBBFh+/btWt3vu3fvYGdnh2rVqmXLPT276iu3++UDytu3b4OIEBoaqtPj/PHHH9DT08PZs2d1sv/BgwdDX19fo1QRqujduzc8PDx0tn9BEHDt2jWMGTMGTk5OICLkyZMHnTt3xp49e7SWzFmZPFgikaBKlSpq5QDMDWJiYtC3b18QERwdHdGjR48Ua1lntctaEARcunQJI0eOxG+//Sbux8fHBy1atICrq6u4f2dnZwwaNAi7d+/Wys10ypQpsLa21ng/GYmLi4OLiwucnZ11kiInNjYWzs7OcHFxQVxcnNb3r5SYmIg8efKgcOHCGqf9+fjxI3bv3o2BAwfC2dlZ/Pu6urqiRYsW8PHxEfNClihRAqNGjcLly5czDW6+7zL39PQU96N8afHx8UGPHj3g6OgIIkK/fv0QExOT1WpJQRAE3LlzB66urnBwcEDdunWRN29edOnSBZ8/f9ZacHbz5k1UrlwZEokEQ4cO1dq44aSkpFTDbh4+fIjZs2cjLCwsV7WEZ8X58+ehr6+vsxySZ8+ehZ6eHoYOHaqT/bPUOKDMhoByx44dICLMmzdPZ8dITExE5cqVUaxYMZ0m2tVFQPltEKNcki5fvnzo3r079u/fr/WxjMeOHcNvv/0GY2NjzJ07N1eO7/ve913WHh4eYtelcuKEi4sLxo4di927d+PJkydZfuAkJibi5MmTGDt2LNzc3MQWLGULZ/Xq1bFq1Sqtr9Si64BSEAR06dIFJiYmOk0Cf/PmTZiYmKBLly5af+i/e/cOU6ZMga2trRjg7du3T2tDCr58+YJVq1ahevXqKYZESKVSuLm5YezYsTh58mSWJ6QIgoAnT55g9+7dGDt2LFxcXCCRSMTjGBkZoWLFiujVqxcWL16MM2fOZDnAFAQBp0+fRu3atVPsv3///hm24GaFXC7HnDlzYGRkhN9++w3nzp3T6v6TkpJw5swZdO/eHfny5QMRwcHBQeXgXlWCIIhDGBITE8UhE9o+j9+/f4+iRYuiSpUqWpvclJa5c+eCiMQlLHVBoVAgMTEx1w3ryQkcUOo4oLx//z7y5MmD1q1b6/yN8unTp7C0tETjxo11dnJrK6BUKBRqdbNqQ3R0NPr06QMiQu3atdVeKi87ZKXL+sWLF/jjjz8gkUhQsWJFtZPfKxQKXL16FbNmzUL9+vVhYmICIoKlpSVat26NJUuW4M6dO7h+/bpOhx/oOqAMDg4GEWH9+vU6O4bSunXrQEQIDg7Wyv4iIiLQq1cvGBkZwdDQEH5+fsiXLx+mTJmi8b4/f/6MHTt2oH379jAzMwMRoUyZMpgwYQJu3LiBO3fuYMmSJWjdujUsLS3F8csNGjTArFmzcPXqVbXvNzdu3EDFihUhlUoxdOhQvHjxIsNZ5iVLlkSbNm0wZcoU7N+/Hy9evEj3fpqcnIxdu3bBw8NDbMFfsmQJbty4gYCAADH5d/v27bXeM3Hv3j3UqlULRIQ+ffroZLKkcvhBr169xB4Je3t7DBs2DOfPn9fKc2bDhg3YsWMHtm7dirlz5yI4OBiXLl3SykukQqFAo0aNYGlpiadPn2q8v4wIgoBWrVohb968Ohvj+OLFC8ydOzfHV0zKDTig1GFAGR8fDzc3Nzg4OODTp09a339aDhw4ACLCtGnTdLJ/TQJKhUKB06dPY8iQIbCzswMRoWDBgujXrx+OHTum0xQzBw4cgJ2dHczMzLBkyZJc8TaZnJyMiIgIrF+/HsOGDdO4y/rcuXNwdnaGvr4+Jk2alG5QLggC7t+/j6VLl8LX1xf58+cHEcHY2Bj16tXDjBkzcPny5Qxbbm/duqX1CVK6DCivXbsGQ0ND9OnTRyf7T0vv3r1haGiIa9euZen3letb161bF0QEGxubFGl/rK2tsxxQxsbGYsuWLWjTpo34AuHm5obJkydnmLpFLpfj8uXLmDFjBurVqyeuLZ8/f374+vrir7/+wv3799MNapKSkjBp0iTo6+vD2dk5w5a8zLrMra2tUbduXQwfPhwbNmxAaGgoJk2aBBsbGxAR6tWrhwMHDqS61qOjozF//nyxN6Rq1arYsmWL1u4/CoUCixcvhqmpKezs7FRa4SerkpOTcezYMfTr1w8FCxYU04L5+/vj9OnTWb7PeXh4iGPllWmHDAwMYGJigv79++POnTtZLvPUqVNBRDqtl299+vQJJUqUgLu7u9Z7VQAgNDQURKRxyqOfAQeUOgwoe/XqpdEDJav+/PNPSKVShISEaH3f6gaU36aqUd7obW1tMWjQIJw8eVLn3c0fPnxA165dxQdMdq1R/L3Muqzt7e3RokULTJgwQaMu6y9fvuDPP/+ETCZDuXLlcOXKFQDAq1evsH79enTv3h1FixYFEUEmk6Fq1aoYO3YsQkJCsjy04N69e1pJ4aSrgFL5QClfvrxOHijp+fLlC9zd3VGiRAm1Xijj4uKwePFicVxhhQoVsH79+lQvE+oGlNHR0diwYQNatmwJIyMjEBE8PDwwffr0LLfWJyQkICQkBP/73/9QtWpVyGQyEBGKFi2K7t27Y/369Xj16hUA4MqVKyhXrhxkMhnGjBmTpfPt2y7zCRMmoEWLFmL3/7eBZuvWrTPtMlemU/Ly8hIDsRkzZmitpenx48fiy0DXrl113oIll8sREhKCgQMHivdaGxsbDBgwACdOnFDrXvttQKn0+vVrTJgwAQUKFBDz4h4+fFit+9SJEycglUoxZswYlX9HG3T5QskB5X84oNRRQPn3339rtctLHcnJyfD09EShQoXEm7m2qBJQJicni8m0lTefjJJp68quXbtQqFAh5M2bF6tWrcqWQezaTgyeVSEhIShWrBgkEkmKVk9XV1f4+/tj7969OumO0yTJvC4Cyuzo8srIgwcPkDdvXrRq1SrT8+/p06cYMWIELCwsIJVK4evri9DQ0HR/T5WA8uPHj1i7di2aNm0KAwMDEBGqVKmC2bNnazVlklJ0dDT27t0Lf39/lClTJsUEHIlEAnt7e5w8eVLj4ygUCuzbtw8+Pj5i4NSrVy9Mnjw5S13m4eHh6NGjBwwNDWFiYoJ+/fppJUAQBAErV65E3rx5UahQIZ2O5fuWQqFAaGgo/P39xd6gAgUKoG/fvjh69GimrbFpBZRKCQkJWLNmDdzc3EBEKF26NJYvX55pZodXr16hYMGC8PLyypFx68uXL9fJkBcOKP/DAaUOAsqIiAidDcpX1atXr1CoUCGtX7zpBZSJiYk4ePAgevbsKXahFi9eHMOHD8eFCxeytR7evn2Ldu3agYjQtGlTrQ/AV9J2l7Umvnz5guPHj2PMmDGoXLmy2FJkYWEBiUQCW1tb7N+/XyfHTs/Tp08xb948VK9eXQymGzZsiJUrV+L9+/epttdFQDlv3jydD8rPzM6dO9OdlCcIAs6ePYu2bdtCJpMhb968GDZsmEot6ekFlO/fv8fKlSvRsGFD6OvrQyKRoEaNGggKCkJkZKQ2PpLK9u/fD1tbW0gkErG7WiaToUqVKhgzZgyOHz+uVqtxbGwsFi1ahJIlS4KIULFiRWzcuDHN4R3qdpnfvHkTL168wMSJE8Xu44YNG+LQoUMa37+eP3+OJk2agIjQrl27NFcr0hWFQoHz589j2LBhsLe3F4co+Pn54d9//02z7jIKKJUEQUBISAhatGgBiUSC/Pnz488//8Tz589TbavLRg5VCYKAzp07a31SHgeU/+GAUssBZWxsLEqVKoUyZcroNG2IKnTRvfBtQJmQkIC9e/eia9eu4o3awcEBo0ePxpUrV7I9mBYEAZs2bYKVlRXy58+PjRs3aq0M2dVlrSq5XI5Lly5h2rRp8PHxEbswrays0LZtWyxbtkxMTq6cACGRSPDHH39k29J133r+/DkWLlyI2rVrQyKRQCaToW7duli2bJmY81DbAeWZM2dyTdqQ79OGJSYmYsOGDahYsWKW0/58G1C+efMGy5YtQ926dSGTySCVSuHp6YlFixbp7IUqI58/f041UUwQBDx48ADLli1D27ZtxZcvIyMj+Pj4YNq0abh06VKaL8BPr6862QAAK0NJREFUnjzBsGHDkDdvXshkMrRt2xZnz55V+xpLq8tcGWR9O8u8R48e6NKlizjswNnZGcuWLdPo2hEEARs2bIClpSWsrKywadOmHLlHXr58GaNGjRJ7TvLly4euXbti79694jAEVQLKbz18+BD+/v7ihKcOHTqkWLZWl8Ow1KGLtGEcUP6HA0otBpSCIIgzJTUZtKxN2h4A3aNHDzg4OKBjx47IkycPiAilSpXC2LFjER4enmMtsi9evEDz5s1BRGjbtm2qxMyqyi1d1mmV686dO1i0aBFatmwpBvCmpqZo2LAh5syZg7CwsHSHEyQnJ2PWrFkwMjJCiRIlcvTG/urVKyxduhTe3t6QSqWQSqXw8vJC06ZNYWlpqZVjKBMbV69ePVckq1cubGBra4s///xTHPfn4+OT5bQ/+fPnR9OmTeHl5QWpVAqZTAYfHx/89ddfeP36tQ4+hWpOnDiBEiVKwMjICLNmzUq3e1WhUCAsLAyzZ89Gw4YNYWpqKgY4LVu2xMKFC7Fx40a0bt0aUqkUFhYWGDFihE5mBme0lrnyOlNOXGvbti0uXbqU5Xvd69ev0aZNGxARmjdvjpcvX2r506hGEASEh4dj7NixKFWqFIi+5vzt2LEjHBwc0KNHD7X3GR0djaCgIDGHbbVq1TBq1CgQEaZPn66DT6G+27dvw8zMTGsLG3BA+R8OKLUYUC5ZsgREhM2bN2uhZNqhjRQNcXFx2LZtG9q1awc9PT1xLN7EiRN1ms9PFYIgYPXq1bCwsEDBggWxY8cOlX83N3VZp+X58+dYu3YtunTpIiaw1tPTQ82aNTFhwgScPn1a7fLcvXsXNWrUABGhf//+WksinVVv375FcHAw6tevL+a7rFmzJubPn5/lZdNyYum1zERERKB9+/bimL6ePXtmaXWuZ8+eYf78+ahZsyaIvuaHbNCgAVasWKH1FbjUFRMTg379+oGIUKNGDdy9e1et309MTMTp06cxduxYODo6ivkp9fT0ULlyZSxfvjzN7lRd+b7LvHLlyil6JQwNDVGpUqUUXebqzBTfvn07ChQoAAsLC6xevTrHE5VHRERgwoQJ4thXPT09tGvXDtu2bVO7t00ul2P37t2oUqWK2PI7ffr0bFlBShWbNm0CEWHp0qUa74sDyv9wQKmlgPLSpUswMDDAgAEDtFQy7VEmka1cubLKAUhMTAw2bdqE1q1bi6lB3N3dUbFiRZQpU0bHJVbN06dPUb9+fRARunTpkuEsyrS6rJXdxDnRZZ2WqKgo7Ny5EwMGDBBXCVKmcxk6dCgOHDiglW4ahUKBhQsXwtTUFEWLFsWhQ4e0UHrNjRkzBubm5mjcuLHYOlS1alXMmTNHrdn5kyZNgkQi0dryfVmVVtqfrl27QiKRIDAwUOX9PHnyBHPmzEHVqlXFiU5NmjSBubk5/ve//+nwE6hOuRyoqakpFi5cmKUW13fv3mHy5MniDOU6depg4sSJ+OOPP8QJIMoekQEDBmDnzp3ZHqAoh5Ao84AqA8vvu8xVTcz+/v17dO7cGUSE+vXr6zwvo6rKlCkDDw8Psd6NjY3RunVrbN68WeWXUOViGzY2Nmjfvr3W0g5pS//+/WFgYIDLly9rtB8OKP/DAaUWAsqoqCjY29ujYsWKWl/VRVsuXLiQ6TJXnz59wrp169C8eXPxJlmxYkXMmDEDDx48AKD7pRdVoVAosHTpUpiZmcHOzi7FZJPc2mWdlvj4eBw5cgQjR46Eh4eH2EJXokQJ9O7dG1u2bNHp4P1Hjx6hTp06ICL06NEjx9ei/XYM5cePHzM9F9Ny9OhRSCQSjB8/PptKnVpmaX/GjRsHqVSKY8eOpbuPBw8eYMaMGeIYS0NDQ7Ro0QLr168XUxBpkodSWz5+/IgePXqAiODt7Z2lmePKAM3IyAhGRkbo1asXIiIiUm339u1bbNmyBb179xZzSEqlUnh4eGDUqFE4cuRIltaQzyq5XI5//vlHvIYKFCiApk2bon379mrPMt+3bx8KFy4MMzMzLF26NMfz5H47hvL+/fuYPn26mCjeyMgo1bmYlsGDB8PAwEAcS6mNtEPalJCQAA8PDxQvXlyjFxMOKP/DAaWGAaUgCGjWrBny5cuHx48fa7dwWrZgwQIQEbZt2yZ+78OHD1i9ejUaN24sphVRtgql9XlyOqB88OABPD09QUTw8/PDuXPncm2X9feSk5Nx7tw5TJ48GV5eXmKgVLBgQbRv3x4rV67M9jyZgiBg+fLlMDc3h62tLf75559sPf630puUk15r+ZQpU1J0q7548QIFChSAj49PjqQlUTXtj1wuh4+PDwoUKJBiwszdu3cxZcoUuLu7i61Cvr6+6bYK5XRAuWfPHtjY2CBPnjwIDg5WKzD4Pu2Pra0tpkyZola3/ePHj7FixQq0b99eDFIMDQ3h5eWFyZMn4/z58zpdLOFbaaUdCg8PV2uW+fnz59GzZ08QETw9PTN8cdK19CblPH78GLNnzxa7sg0MDNC4cWOsXr06RQ/R1q1bQURYtGhRqn1kNe2QLjx69AgWFhZo3rx5lgNbDij/wwGlhgHlzJkzQUTYu3evlkumfYIgoE2bNjAzM8PkyZNRv3596OnpQSKRqDxuLacCyo8fP2Lw4MHQ19eHmZkZHB0dc12X9fcEQUBERATmz5+PZs2aiZOYzM3N0bRpUwQFBYmzX3NaZGQkGjVqBCJChw4dcmQ8niqzvL8dz6ucKOHq6orx48ejfPnysLW1zfKErKzIatqfN2/ewNbWFh4eHhg3bhxcXV3FyR+///47tm/fnum4tZwKKN+9e4cOHTqIrUzqjFNNK+3Phg0bNH7RU3ZFBwUFicMBlJNMmjVrhvnz5yMiIkLn19qbN28yTDukyixzR0dHmJmZQV9fH4MHD862Vda+pcos78jISAQFBaFGjRqQSCTQ09ND/fr1ERgYCDMzM/z+++8Z1rc6aYd06Z9//gERYdasWVn6fQ4o/8MBpQYB5alTpyCTyTBy5EgdlEy7Xr9+jaVLl6J27drizatWrVpYvHixWrMMdR1QptVlrVzZRdnF5erqmiu6rNPy9OlTrFq1Ch07dkShQoXEt3hPT08EBgbi7Nmz2dZqoi5BEPD3338jX758sLa2xtatW7P1+OqmDYqPj8euXbvQsWNHsXW9WLFi2ZJxIKtpf76dWatcw97AwACdOnXC7t271Wqlye6AUhAEbN26FdbW1siXLx/WrVunch1rK+2PqpKTk3H27FkEBgbC09NTPD8KFSqEjh07YtWqVTodr5iQkIC1a9eKrc2lS5fOMO1QVFRUilnmrq6u4hAY5Xmt6lrm2qBu2qCXL19i0aJF4mQxIkLt2rWxdOlSlTIOZJZ2SNdGjBgBmUyG06dPq/27HFD+hwPKLAaUyhaGWrVq5doA4cWLF2LuP2Vakbp162Ls2LEwMjJCz5491d6nNgPKzGZZ582bF8WLF4dMJkOhQoWwevXqHO2yTsv79++xbds29OnTRxyrKZFIUKFCBYwYMQKHDh3KkbyPmnj16hVatmwJIkLr1q2zLRFxVvNQ7tmzB0SE7t27p8iJWrJkSa3nRH337h2mTJmiVtofQRBw5coVjB49WmyZs7CwQLdu3dC9e/cs93BkZ0D56tUrtGrVCkSEVq1aqXROCIKA0NBQ+Pr66jztT2Y+f/6MQ4cOYcSIEahQoYI4g9zBwQF9+/bFtm3b0ky2rylBEHDy5Em0bNkSEokElpaWGD16tEqtuomJiVi1ahUKFiwImUyG4sWLI2/evOl2mas7yzwj6gaUSj169ICxsTHGjh0LHx8fMSdq7dq1sXDhwkxzoqaVdmjr1q06f8YmJyejZs2aWerh4IDyPxxQZiGglMvl8Pb2RoECBXIsh1h6IiMjxdVJJBJJuquTrFq1CkSENWvWqLX/rAaU6s6yPnjwICpUqACpVIoRI0bkyPiatMTFxeHgwYMYNmwY3N3dxQeTo6Mj+vXrhx07duh8zd7s8G1rlKWlpVqtUVmVlYAyrTFQ367aZGlpCSLNV22KiIhAr169YGRkBENDQ/j5+WWY9kcQBFy4cAHDhw9H8eLFQZRydRLli5EmY7CzI6D8vtX62/HX6UlMTMT69evFSRyOjo5YsmRJji/08K0PHz5g+/bt6Nevnzh5SiKRwN3dHcOGDcO///6r9fI+fPgQAQEByJMnD/T09NC+fXtcuHAh09+Lj4/H8OHDIZVKUaFCBRw8eDDTxOzfzjLPSmaIrASUq1evTvVMeffuHVasWIEGDRqIw6tUWbVJmXZIOV6+SJEimDlzpk5n9Wd1DDYHlP/hgDILAaUqszSzU1bXT+7evTuMjY3VyoeXWUCp6SzrxMREjBs3Dnp6enBxccnWbo+0JCUlITQ0FBMnTkStWrXEmZs2Njbo3Lkz1qxZk2tyHerCt+PlGjdurNPPqm5A+e0szfSGPSQlJYnryltbW4sPJ1XWlU8r7c/kyZPTnXmvUChw5swZBAQEiMM0VFk/WZklwsPDQ60sEboOKJ89eyaOq+3YsWOm42q/T/tTr149HDhwIMdnLKsiMjISa9asQadOncTy6+vro1atWpg4cSJCQ0O1liA/JiYGCxYsEGeqV61aFVu2bMm0Fe7ChQtwcXGBnp4exo8fn6K35vsuc3VnmX9P3YDy+vXrMDY2zrDXKyoqCmvWrEGTJk3EIQiVK1fGrFmzMswOcO3aNXTr1i1b0g5lJUsEB5T/4YBSzYDy0KFDaueR04X79+9j2rRpqFChgvhm2rJlS2zYsAHR0dEq7ePz588oW7YsnJycVM4t9m1Aqe3E4JcuXUKZMmWgp6eHcePG5UgKJoVCgfDwcMydOxeNGzeGmZmZ2P3eokULLFy4ELdu3coVE2my0z///ANbW9sszehVlboBpbp55ORyOU6cOIEBAwaI41ttbW0xaNAgnDx5UmyVyCztz/f7PHnyJAYNGiR2g9vY2GDgwIEICQlRuaXj8uXLauex1VVAqZz5nydPHpVm/qua9udHIQgCbt26hYULF6JFixZiN7OZmRkaN26MuXPnIjw8XONA+fu0Q0WKFMGMGTMy7OFISEjA2LFjoaenB1dXV1y6dCndbbOylrkyqFUnoIyOjoajoyPKlSunck/Sp0+fsH79erRo0ULMdlGhQgVMmzYN9+/fT/N3sivtkDKPrar5eTmg/A8HlGoElM+ePYOVlRUaNGiQI2/dt2/fRmBgIMqVKwcigomJCdq0aYMtW7ZkOeH1vXv3YG5ujnbt2mV4YSq7rKtXrw4rKyutJgaPj4/HyJEjIZVK4e7ujrCwsCx9lqx69OgRgoOD0a5dO7EVy9DQEN7e3pg6dSouXLiQa8fJZqePHz+KaU2ymnMwI+oElJqudCGXy3H69GkMGTJEXIXI2toabm5uMDU1hUQiSTftT3JyMo4dO4Z+/fqJs3nt7Ozg7++P0NDQLN8b1F1pSxcB5aNHj+Dt7Q0iQs+ePdNt+f2+9TYraX9+FMnJybhw4QKmTp0Kb29vMQCytrbG77//juDgYI2vhbTSDmUUoFy7dg3u7u6QSqUYOXIkvnz5otJxVF3L3MrKCtWrV8+0y1wQBLRt2xbm5ua4d++e2p8b+Pps2bx5M3x9fWFiYgIiQrly5RAYGJhmHSgnPCnTDrm4uGg17ZC6K21xQPkfDihVDCiVa/Ha2dll201TmQpj/PjxcHFxEd+S27dvjx07dmhtsse2bdvEnGGZdVlLpVIYGxtrbZZ1aGgonJycYGBggKlTp2bLustv3rzBpk2b4OfnJ45vk0qlqFSpEkaPHo1jx46pfIP+FSlXRTExMcGCBQu09nKlakB5+/ZtmJqaamUtXuXEEW9vb0gkEnFMrKWlJXr16oVDhw4hKSkJSUlJOHToEHr16iW2wtvb22PYsGE4f/68VupAEAS0b98eZmZmKnXpaTOgVCgUWLBgAUxMTFCsWLF0VxlSpv1Rtt56eHhoJe3PjyQ+Ph5Hjx7F6NGjUalSJXE2dvHixeHn54fNmzdneUGCzNIOfSspKQlTpkyBgYEBnJyccObMmSx/pu+7zI2NjcXPlVGX+cKFC0FE2L59e5aP/a24uDhs374dv//+u9g75OLigvHjx6dKsabLtEPv3r2DnZ0dqlWrlukziQPK//zyAeXV6zehX6A41uwNQcSLT4hLSLsl6o8//oCenh7Onj2r0/IIgoCwsDD873//Q6lSpcRcap07d8aePXu0Guh822Vdvnx5SCSSFLMIv++yPnfpKtr2/gPl6jTPsK5UERcXhyFDhkAikaBKlSq4deuW1j7X92JiYrBv3z4EBASgbNmy4udzdnbGoEGDsHv37lyVeuhHEBMTg/79+4Moa+s2fy8uIRkBk+agYOnKGZ5bcXFxcHFxgbOzs0bLUKaX9icmJgaXLl3CyJEjxZcNAwMDcczXb7/9hlGjRuHy5cs66faPjY2Fs7MzypQpk+ELY1xCMgo4lceQSfM0vhbv3r2L6tWrg4gwYMCANIe/fJ/2p02bNjhz5swvN/QjLR8/fsTu3bsxcOBAODs7i/eXsmXLIiAgAPv27VN5SJGSOmmHbt68icqVK0MikWDIkCEaTyaKS0iGm2cT+PYZhp0nLmLZqrS7zC0sLMSMFtqeZQ58Ddx3796NTp06iTl8nZycMGbMGFy7di3FuaeLtENnz56Fnp4ehg4dmu42cQnJWL8/BAY2jth3Jkyj6/BnIAEA+sXcfxNLGy5E0om7bykyKp6+rQAJERW1NCEvpwLUsXJRKlnQnHbt2kWtWrWioKAgGjJkiNbLA4Bev35Nt2/fpjt37lBUVBQZGRmRk5MTOTs7k729Penp6Wl0jNjYWLp+/TqFhYWJXxEREZSQkEBERMWKFaOYmBgSBIEWLVpENWvWpKJFi9KDt3Fq1ZUqjh8/Tn5+fvT69WuaMmUKDR48mGQymUaf71tJSUl0/vx5OnbsGB09epQuXrxIcrmcihQpQt7e3uTt7U116tQhW1tbrR3zV3Xy5Enq2bMnvXjxgiZNmkQBAQEqn6vqXocAqFu3brR9+3a6dOkSlS5dWu3yvn//npYvX06JiYnk6+tLBQsWJHNzczIyMiKJREIA6MuXL+KXIAgklUqJiMT/NzY2Fr8kEonaZcjMrVu3qGLFitSmTRtavXq1eAx16yszcrmc5s2bR+PGjSM7OztauXIl1apVS/w5ADp79iwFBQXRzp07KU+ePNS7d28aMGAAFS1aVMuf+ufx8uVLOn78uHj/ef78Oenp6VHlypXF+0+VKlXIwMAg030BoNOnT9P8+fNp9+7dZGFhQX369KH+/fuTnZ2duJ1CoaD58+fTmDFjyNbWloKDg6lOnToql1nVc6tDpSJkmPiRTp8+TQMHDiSpVEp58uShp0+fEhGRkZERubq6kpubm/hVtmxZMjMzU7ksaZHL5fT48WO6c+cO3b17lxISEihfvnzk7OxMpUqVIhsbG5JIJJSYmEjh4eF06dIl+vjxI9nZ2VGlSpXIyckpS8+YoKAgCggIoF27dlGLFi3Uqit1nok/i18qoHwWFU9/7rpBpx+8J5lUQgoh/Y+u/HmFwiZ0fHov8q7iRtu2bdPaAwRfW4dJEATx/4mIpFIpSaVSkkgkWToWAHr58mWKwDEsLIwePHhARET6+vrk4uKS4oIvV64cWVhYUGRkJLm7u1O1atVo0epN9L89N9Wqq5oOVjS1pSsVsTRJc7vo6GgaMWIELV++nGrXrk0rVqwgBwcHtT/j9wRBoPDwcPEGfvr0aYqPjydLS0vy8vIib29v8vHxIQcHB50EAL+6+Ph4Gjt2LM2bN488PDxo1apVVKZMmXS3z8p1WNPBisom3aIR/XvQ+vXrqWPHjmqV8ebNmzR//ny6dOkSXbp0ifT09AiAGERqgzbPrfXr11Pnzp1pxYoVVK9l+yzVV0bXYkREBPXo0YOuXLlCAQEBNGnSJDIx+bptUlISbdu2jYKCgujy5cvk6OhI/v7+1KVLFzI1NdXaZ/wVAKD79+/TsWPH6NixY3TixAmKiooiExMTqlWrlhhglitXTnxxSc/jx49p0aJFtGLFCoqPj6c2bdqQv78/VapUSdzm/v375OfnR6dOnaI+ffrQzJkzKU+ePOnuMyvXYg2H/PR233y6evoIXbt2jYoUKUIfP35M1WBx8+ZNSk5OJolEQg4ODuTm5kaDBg2iGjVqiPvM6jNO+ewUBEH8/rfPTuV2CoWCAJBMJiOZTEZyuVytxhkA1KZNGzp69CjtDzlPf12J1up1+LP5ZQLKzZciafw/N0kuIMMTIRUIRIKcxjcpTd1rOemugFqgUCgoPj6eSpYsSW/evCELC4sUgaObmxs5Oztn+GZ88OBBajsqiAo2HkSQSNWqK5lUQnpSCU1s5kK/V0zZgnHw4EHq3bs3ffr0iWbOnEl9+vTJ9AaaHgD04MGDFDfpDx8+kLGxMdWsWVMMIN3c3LJ8DKa+8+fPU48ePejBgwc0duxYGjVqFOnr66fYJqvXoUxCJE9KpDJJd2j/gj9V+h1BEOjff/+loKAgOnLkCNnY2NCzZ89SPHRysz59+tC2Ky/IuuEA9esrnWsxOTmZpk+fToGBgeTg4ECrVq2iKlWqENHX1ttly5bR4sWL6dWrV1SvXj3y9/en+vXr83WkJQqFgsLCwsR71+nTp+nLly+UP39+8vLyIh8fH/L29qYSJUqke47GxsbSmjVraP78+fTw4UOqWrUq+fv7U6tWrUhPT48EQaC//vqLRowYQfny5aPly5dTw4YNU+0nq9eilEDy5CTq4mJEk7s3Sne7pKQkun37thhgFilShP744w+Vj6MLcrmcnj17RklJSeTkpNrzPDo6msr7DiShvC9J9fS19kz8Gf0SAeWiE/dp9uF7Gu9nWD1HGuhVUq3fUQZ5ZmZm2fIQA0A3btygvHnzUtGiRdU+prbrKioqigICAujvv/+mevXq0fLly6lYsWJq7+/169fiTfjYsWMUGRlJMpmMKlWqJN6Eq1SpQoaGhhqXnWVdQkICBQYG0owZM6hMmTK0evVqcnd3JyJtnFsgIkmm1+Hnz59p7dq1NH/+fLp37x5VqFCBAgICqGnTphm21uhCfHy82PKnrqDDtynoxCONy6Csr6tXr1KPHj0oIiKCRo0aRWPHjiVDQ0OKiIig+fPn0/r164mIqHPnzjRkyBBycXHR+NgsY4mJiXT+/Hk6evQoHTt2jC5evEgKhYKKFi0qtl56e3tToUKFUv2uQqGgAwcOUFBQEB0/fpyKFClCAwcOJD8/P7K0tKQnT55Q79696ciRI9S1a1eaO3cuWVpaElHOPROVvQI5zdnZmX777Tfy9/cnHx+fDMuUk/HDj+anDyg3X4qkUTtvaG1/M1q5UrtM3jTkcjmdPHmStm/fTocOHaJHjzR/KGQHbddVu+JyWjuuDyUkJNC8efOoW7duKt9MoqOj6eTJk2I39q1bt4iIyNXVVbzJ1qpVK9sDBKaaq1evUvfu3enmzZs0atQoKtWoB/1v722t7T+t6zAyMpIWL15My5cvp5iYGGrVqhX17NmT3rx5Qzt27KBRo0ZRtWrVtFYGVZw5c4ZmzJhBvr6+1LRpU8qXL59Kv6fta7Gy5AHtmDlUDPLLlSuXovXW1taWBgwYQL179yYrKyutHZepJyYmhk6dOiXe9yIiIoiIyMXFRbzv1a5dm/LmzZvi965fv07z58+nDRs2kEwmo65du9LgwYPJycmJVq9eTX/88QcZGxvT0qVLKaFw+Wx/JuYmAOj8+fPUv39/CgsLIxcXFxoyZAh16tSJjI2NU2ybE/HDj+ynDiifRcWTz7yTlCgXMt9YRYZ6UjoaUDvVmIjk5GQ6fvw4bd++nXbt2kUfPnyg4sWLU8+ePWnMmDFaO76uaL+uQEJyEpV+vINWLZyV6QSYhIQEOnfunHgjvXz5MikUCrK3t08xkaZgwYJaKh/TtaSkJJoxYwZNnb+MCvVcTJBqNrHsW8rr0C6fMZ0/f56CgoJox44dZGZmRp06daJixYrRiRMn6OjRoySXy6l69eq0a9cuyp8/f7a1kACgDx8+UIsWLejMmTOkr69PPj4+5OvrS82bN6f8+fOn+XtavxYBgjyJfs/zgEYN6kWbNm0SW289PDwoICCAfH19VZokwrLXmzdvUkzwefr0KclkMqpYsaJ4X6xatSoZGRkREdHbt2/pr7/+oiVLltCbN2+oYcOG5O/vT6VLl6Z+/frRv6cvUbH+K0gO7V0D6T0Tc6vk5GSaOXMmPXr0iJycnOjMmTO0d+9esrS0FCc8FS5cOFvjh5/FTx1Qdl55gc4++qDemMlMyKQSqvZbflrXszIlJibS0aNHafv27bRnzx76+PEjOTg4UJs2bcjX15fc3d1zRfO+KnRRV1IJUbUSVrS+Z+VUP1MoFHT16lWxCzs0NJQSEhLIysqK6tSpI46D/O2337RWHpYzWi04TmGvv5AWTy2SSSVU3CSZYv+ZShcvXqTixYtT5cqV6e3bt3Ty5EkCQLVq1SJfX19q2bJljs/of/HiBe3atYu2b99Op06dIqlUSnXq1CFfX19q0aIFFShQQNxWV9eitRBF95YNppiYGGrdujX5+/tT1apVf5h71K8OAD169Ei8Zx4/fpzev39PRkZGVKNGDXHoj7u7O8nlctqyZQsFBQXRtWvXqHTp0jR48GDa9cmO7kcTKbR8LSqfiT8CAHT48GEaOHAgPXjwgCwsLKhOnTqkUCjo+PHj9OXLF2rbti3FeXSjiPfJOosffkY/bUB5/00s1Q06pbP9V3h9gI7uXE8xMTFUqlQpMYgsU6YMvXr1ShyIHBkZScuWLVNpn/b29uTv70/+/v7i90JCQmjevHl08eJFiomJoZIlS9Lw4cPVnuWaEV3X1dGAWlTC2ozu3r2bYiLNp0+fyNTUlGrVqiXeDF1dXXkCwE9E1+eWwdEZZJwUTRERESSRSMjLy0sM0jRpzU7rWpwwYQJNnDgx1bYmJib0+fNnlff9+vVr2r17N23fvp1OnDhBRES1a9f++hJauyG1X38ry+XOTAPFJRo9oHuWxjGz3EUQBLpx44Y4/vLUqVP0+fNnsrCwELNbeHt709u3b2n+/Pm07/QVsum5WGflORpQixwK6C5NzpMnT6h48eJ07do1cnNzE7+/Zs0a6t69e4ptDQ0NxZR43xMEgeLi4sjMzIxu3LhB27dvp23bttHdu3fJ3NycHB0d6UWsggxbTdbZZ9F1XeUU7fVB5TIbLkRmOrU/qyAo6MYXC/L396cKFSpQbGwshYWF0dChQyksLIzev39PREQWFhbk4+Oj0bHOnj1LZcuWpZEjR1LBggVp37591KVLF8qbNy81adJEGx9Hp3UllRB1DVxJT3fNphcvXpC+vj5VqVKF/P39ydvbmypVqsRdbT8xXV+HUZYuVFH6hAYPHkzNmzfX6fi/YcOGUd++fVN8z9vbmypWrKjWfgoVKkR9+/alvn370rt372jPnj20fft2GjJkCNk0eUj6pb11Ul8yCVGhGm04mPxJSKVSKleuHJUrV46GDh1KSUlJdPHiRbF73N/fn+RyORUuXJi8vb3Jd1QQnX+v3dZJJZlUQuvPR9KEZppP5PL09KRu3bpRt27dVP6dPHny0N27d8V/Z9TqrlAoaMaMGRQcHCxmPxk7diyZm5vTlStXaOfOnZRYtBoZQiCSaL9xQ5t1ldv8tC2UtWedoKdR8Trbvyz+A71c3kd8C7K3t0+VokedWdaenp508uTJFN9L70/TuHFjKliwIK1atUqzD/H/dF1X0s8fqJXBdfL29qaaNWtqnOSW/Th0fW4VsTCi0yO9tbpPVa/F8PBwcnNzo1OnTlHNmjU1Pm5UVBQ1XnqJXsXJNd5XeorlN6GTw7x0tn+We8TFxdHp06fFXqFYz6EkN1JtUlhWaOvcSi+g/P5ZWrt2bQoJCaE1a9aQv78/ffr0SaX9A6A7d+7Q1q1bxZ7EJ0+eENF/idmja/1Bifq6a0H8Wa/Dn7KFMi5RTpE6fIgRESmMLWnS1BlUqXw5MTG4Jnbu3EnlypWj3r17U69evTLcNjo6mpydnTU6nlJ21BVM89PECdPJ1PCnPN1YOrLj3Hr+KYE+J8q1em6pei2uWLGCHB0dtRJMEhEZmOah1zoMJomIIj/Ea72+WO5kZmZGDRs2pIYNG1JcopxcJxzS6fF0fW5dvHiRKlWqREePHiUXF5cUPVtxcXFUrFgxEgSBypf/v/buLjSq9I7j+O9kxtmNcVATM2WSJkaMSaMoWFi2meKFNwvGGNGA22IwCr4VRG/aor2odIQRQRCCN0EICg20NsVWCtpAGXVB0roIJc2N8SW6hibbNRBj4gt56YWdqdmdlzN55kwyJ98PeDEzD+dM/vyfMz9nznnODxWJRJIue2VZlurq6nT69On4cx8uzP7lP/+lL7zOfunh1nnorr/mf56+GJfjX7talnoHhvTscb+6urqSDluxYoXOnDmTdnPFxcXyeDzy+/0J1xyLuXr1qu7du5fyvMz+/n61tbWl3ackjRb4NbP0x7bGztWMpJ/98tdaPj3m6H6wsOSqtxo+b9XHr79JO7a9vV2rV69O+6uBnbn45s0bdXZ26uTJk8nf28yMBgYGvvMzeTJvl5Zq5gc/tTV2rpiLi9N8H+dXrlypcDhstP3S0lJJUklJyax5WVtbq46ODm3atEmjo6M6f/68QqGQ+vr6Zt2eMia2fmd3d3fC/Vj+UsnhC9VmJA28GNeGsuVpx+YTVwbKd1m8zD+V3//hj3r379QLnpaXlycMlJ2dnTpy5Ej88Y0bN9LuLxqN6sCBA7p06VLKRYcHBwd18eLFtNuTJF+wRsFWZw80kr1awV1y1Vs9//jSVm+9evUq4fNzmYvXrl3T2NiYWltbU44bHx9P+sH1bb5gjYIOB0qJubgYzfdxvqKiImmgjEQiikQi8cevX79WT0+Pjh07Fn8utg5xIvX19aqvr48/DoVCqqurU3t7e8LP3unpafX09CT9jMxVrXKVU3LJlYHS583NVcJ/6/6ragKp15NKdsVyU1OTPv30/0sHlJeXp9zO7du3tWPHDl24cEH79u1LOTYUCml4eDjlmJgHX0+opbPP1lgTdmoFd8lVb/3lz39S9aqP045LtnRQpnNRev9zd2NjY9oryWtqamzf2ODRyFsd7Hpka6wJ5uLi8+A/E2r57fwd51Ot3HH06FHt2bMn/njv3r1qbm7W7t2748+VlZXp+fPntt7DkiVLtHnzZj18+DDh616vV6dOndKJEycSvp6r41auckouuTJQVpUUyZIc/dnbkrR53ffnfA6E3++X3z/7pF+fz6epqanvjL1165YaGxt17tw5HT58OO22fT7frHXtUilaPilLfQu6VshPueqt0KZ1Rr2VyVyUpCdPnigajer69eup35tlyefzac2aNbbeR6BsUlbXI+Yism4hH+eLi4vjt4SUpMLCQgUCAVVXV88aFztnMtm8jJmamlJvb68aGhLfZ9yyLC1btizpxaG5qlVVSZGDe5gf7ovIkoo+8qrS4ZXoK0uWZv2gXFVVpTt37mhwcDC+9FA0GtX27dt1/PhxNTc3a2hoSENDQxoZGcnKPvO1Vlj48rm3Es3FmI6ODgWDQW3bti2r+8znemFhc0NvBQIBFRYW6ubNmxoeHtbo6KgkKRwOq7u7W48fP9b9+/fV0tKip0+f6uDBg3PajxtqNV9cGSglaWttQJ4CZ06s9RRY2lpj7xvATITDYQ0MDGjt2rXxE5CvXLmiiYkJnT17VsFgMP7vw58DTOVjrZAf8rW3Es1F6f35V5cvX9b+/fvl8Xiyvt98rRcWvnzvLa/Xq7a2NrW3t6usrEw7d+6U9P4K7UOHDqmurk4NDQ16+fKl7t69q/Xr1895X/leq/ni2nUoc3H3F7esdE+t4BR6KzPUC06ht+yjVnPj2m8o133Pry3Vq7L+vwxPgaUt1atc1QzUCk6htzJDveAUess+ajU3rg2UkhTZtVHeLDeEt8BSZNfGrG5zIaBWcAq9lRnqBafQW/ZRq8y5OlBWFC/Vb7J8v8xw0wZVOHzC7nygVnAKvZUZ6gWn0Fv2UavMuTpQStJPPqnUzz+rycq2fvFZrT7/pDIr21qIqBWcQm9lhnrBKfSWfdQqM669KOfbfnfvmU5f79Pk9Iympu3/yZ4CS94CS+GmDa5vhhhqBafQW5mhXnAKvWUftbJn0QRKSfpqZEK/utarLx5+I0+BlbIxYq9vqV6lyK6Nrv6aOhFqBafQW5mhXnAKvWUftUpvUQXKmP7hMXX+/ZmiD77WsxcTs1bEt/R+0dGtNQG1/KjStVdj2UWt4BR6KzPUC06ht+yjVsktykD5ofG3kxp4Ma53k9PyeQtUVVLkyhXss4FawSn0VmaoF5xCb9lHrWZb9IESAAAAZlx/lTcAAACcRaAEAACAEQIlAAAAjBAoAQAAYIRACQAAACMESgAAABghUAIAAMAIgRIAAABGCJQAAAAwQqAEAACAEQIlAAAAjBAoAQAAYIRACQAAACMESgAAABghUAIAAMAIgRIAAABGCJQAAAAwQqAEAACAEQIlAAAAjBAoAQAAYIRACQAAACMESgAAABghUAIAAMAIgRIAAABGCJQAAAAwQqAEAACAEQIlAAAAjBAoAQAAYIRACQAAACMESgAAABghUAIAAMAIgRIAAABGCJQAAAAwQqAEAACAEQIlAAAAjBAoAQAAYIRACQAAACP/Bc866gMaMupVAAAAAElFTkSuQmCC", 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", "text/plain": [ "
" ] @@ -974,6 +1000,9 @@ "bits_precision_ideal = 16\n", "bits_precision_current_limit = 16\n", "\n", + "#This determines if we want to extrapolate our RE or want to calculate it explicitly\n", + "extrapolate = True\n", + "\n", "E_min_ideal = -len(ham_ideal.terms)\n", "E_max_ideal = 0\n", "omega_ideal = E_max_ideal-E_min_ideal\n", @@ -1014,22 +1043,33 @@ }, "outputs": [], "source": [ - "metadata_current_limit = EstimateMetaData(\n", + "metadata_current_limit = GSEEMetaData(\n", " id=3000,\n", - " name='FermiHubbard_ideal_Current_Limit`',\n", + " name='FermiHubbard_Two_Band_Current_Limit`',\n", " category='scientific',\n", " size=f'{6}x{7}',\n", " task='Ground State Energy Estimation',\n", - " implementations=f'GSEE, evolution_time={t_current_limit}, bits_precision={bits_precision_current_limit}, trotter_order={trotter_order_current_limit}',\n", + "\n", + " evolution_time=t_current_limit,\n", + " trotter_order=trotter_order_current_limit,\n", + " is_extrapolated=extrapolate,\n", + " bits_precision=bits_precision_current_limit,\n", + " nsteps=trotter_steps_current_limit,\n", + " implementation=\"GSEE\"\n", ")\n", "\n", - "metadata_ideal = EstimateMetaData(\n", + "metadata_ideal = GSEEMetaData(\n", " id=4000,\n", - " name='FermiHubbard_ideal_Ideal',\n", + " name='FermiHubbard_Two_Band_Ideal',\n", " category='scientific',\n", " size=f'{20}x{20}',\n", " task='Ground State Energy Estimation',\n", - " implementations=f'GSEE, evolution_time={t_ideal}, bits_precision={bits_precision_ideal}, trotter_order={trotter_order_ideal}',\n", + " evolution_time=t_ideal,\n", + " trotter_order=trotter_order_ideal,\n", + " is_extrapolated=extrapolate,\n", + " bits_precision=bits_precision_ideal,\n", + " nsteps=trotter_steps_ideal,\n", + " implementation=\"GSEE\"\n", ")" ] }, @@ -1043,31 +1083,31 @@ "output_type": "stream", "text": [ "Estimating Current Limit\n", - "Time to generate circuit for GSEE: 4.75410015496891e-05 seconds\n", - " Time to decompose high level HPowGate circuit: 9.162499918602407e-05 seconds \n", - " Time to transform decomposed HPowGate circuit to Clifford+T: 0.00022454099962487817 seconds\n", - " Time to decompose high level IdentityGate circuit: 1.4999999621068127e-05 seconds \n", - " Time to transform decomposed IdentityGate circuit to Clifford+T: 4.249999619787559e-06 seconds\n", - " Time to decompose high level PhaseOffset circuit: 0.00012683400018431712 seconds \n", - " Time to transform decomposed PhaseOffset circuit to Clifford+T: 0.00012849999984609894 seconds\n", - " Time to decompose high level Trotter_Unitary circuit: 0.7423197500011156 seconds \n", - " Time to transform decomposed Trotter_Unitary circuit to Clifford+T: 2.832495917000415 seconds\n", - " Time to decompose high level MeasurementGate circuit: 0.0022889159990882035 seconds \n", - " Time to transform decomposed MeasurementGate circuit to Clifford+T: 5.5915999837452546e-05 seconds\n", - "Time to estimate Current Limit: 7.096430375000637\n", + "Time to generate circuit for GSEE: 0.00012049998622387648 seconds\n", + " Time to decompose high level HPowGate circuit: 0.00010195799404755235 seconds \n", + " Time to transform decomposed HPowGate circuit to Clifford+T: 0.00022904202342033386 seconds\n", + " Time to decompose high level IdentityGate circuit: 2.5374989490956068e-05 seconds \n", + " Time to transform decomposed IdentityGate circuit to Clifford+T: 5.208014044910669e-06 seconds\n", + " Time to decompose high level PhaseOffset circuit: 9.14589618332684e-05 seconds \n", + " Time to transform decomposed PhaseOffset circuit to Clifford+T: 0.00010649999603629112 seconds\n", + " Time to decompose high level Trotter_Unitary circuit: 0.6369308329885826 seconds \n", + " Time to transform decomposed Trotter_Unitary circuit to Clifford+T: 2.6309287089970894 seconds\n", + " Time to decompose high level MeasurementGate circuit: 0.0021917499834671617 seconds \n", + " Time to transform decomposed MeasurementGate circuit to Clifford+T: 4.954199539497495e-05 seconds\n", + "Time to estimate Current Limit: 6.172279916994739\n", "Estimating Ideal\n", - "Time to generate circuit for GSEE: 4.9416999900131486e-05 seconds\n", - " Time to decompose high level HPowGate circuit: 0.00010812499931489583 seconds \n", - " Time to transform decomposed HPowGate circuit to Clifford+T: 0.00021195800036366563 seconds\n", - " Time to decompose high level IdentityGate circuit: 1.1208001524209976e-05 seconds \n", - " Time to transform decomposed IdentityGate circuit to Clifford+T: 3.499999365885742e-06 seconds\n", - " Time to decompose high level PhaseOffset circuit: 6.333400051516946e-05 seconds \n", - " Time to transform decomposed PhaseOffset circuit to Clifford+T: 8.758300100453198e-05 seconds\n", - " Time to decompose high level Trotter_Unitary circuit: 0.5947406670002238 seconds \n", - " Time to transform decomposed Trotter_Unitary circuit to Clifford+T: 2.3166216659992642 seconds\n", - " Time to decompose high level MeasurementGate circuit: 0.0024056670008576475 seconds \n", - " Time to transform decomposed MeasurementGate circuit to Clifford+T: 5.245800093689468e-05 seconds\n", - "Time to estimate Ideal: 6.372025291000682\n" + "Time to generate circuit for GSEE: 4.7291978262364864e-05 seconds\n", + " Time to decompose high level HPowGate circuit: 8.358299965038896e-05 seconds \n", + " Time to transform decomposed HPowGate circuit to Clifford+T: 0.0001830410328693688 seconds\n", + " Time to decompose high level IdentityGate circuit: 1.591700129210949e-05 seconds \n", + " Time to transform decomposed IdentityGate circuit to Clifford+T: 3.915978595614433e-06 seconds\n", + " Time to decompose high level PhaseOffset circuit: 7.058301707729697e-05 seconds \n", + " Time to transform decomposed PhaseOffset circuit to Clifford+T: 8.283299393951893e-05 seconds\n", + " Time to decompose high level Trotter_Unitary circuit: 0.5475135830347426 seconds \n", + " Time to transform decomposed Trotter_Unitary circuit to Clifford+T: 2.4883924159803428 seconds\n", + " Time to decompose high level MeasurementGate circuit: 0.002176332985982299 seconds \n", + " Time to transform decomposed MeasurementGate circuit to Clifford+T: 5.570799112319946e-05 seconds\n", + "Time to estimate Ideal: 6.056912083993666\n" ] } ], @@ -1077,13 +1117,14 @@ "\n", "estimate_current_limit = gsee_resource_estimation(\n", " outdir='GSE/FermiHubbard/',\n", - " numsteps=trotter_steps_current_limit,\n", + " nsteps=trotter_steps_current_limit,\n", " gsee_args=current_limit_args,\n", " init_state=init_state_current_limit,\n", " precision_order=1,\n", " bits_precision=bits_precision_current_limit,\n", " phase_offset=phase_offset_current_limit,\n", - " circuit_name='three_band_current_limit',\n", + " circuit_name='two_band_current_limit',\n", + " is_extrapolated=extrapolate,\n", " metadata=metadata_current_limit,\n", " write_circuits=True\n", ")\n", @@ -1094,13 +1135,14 @@ "t0 = time.perf_counter()\n", "estimate_ideal = gsee_resource_estimation(\n", " outdir='GSE/FermiHubbard/',\n", - " numsteps=trotter_steps_ideal,\n", + " nsteps=trotter_steps_ideal,\n", " gsee_args=ideal_args,\n", " init_state=init_state_ideal,\n", " precision_order=1,\n", " bits_precision=bits_precision_ideal,\n", " phase_offset=phase_offset_ideal,\n", - " circuit_name='three_band_ideal',\n", + " circuit_name='two_band_ideal',\n", + " is_extrapolated=extrapolate,\n", " metadata=metadata_ideal,\n", " write_circuits=True\n", ")\n", @@ -1127,7 +1169,7 @@ ], "metadata": { "kernelspec": { - "display_name": "qca", + "display_name": "qc-apps", "language": "python", "name": "python3" }, @@ -1141,7 +1183,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.12.0" + "version": "3.11.10" } }, "nbformat": 4, diff --git a/notebooks/MagneticLattices.ipynb b/notebooks/MagneticLattices.ipynb index ad17dfe..4951a0b 100644 --- a/notebooks/MagneticLattices.ipynb +++ b/notebooks/MagneticLattices.ipynb @@ -52,7 +52,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "/Users/jonhas/anaconda3/envs/other/lib/python3.12/site-packages/cotengra/hyperoptimizers/hyper.py:33: UserWarning: Couldn't import `kahypar` - skipping from default hyper optimizer and using basic `labels` method instead.\n", + "/Users/gsgrattan/.conda/envs/qc-apps/lib/python3.11/site-packages/cotengra/hyperoptimizers/hyper.py:33: UserWarning: Couldn't import `kahypar` - skipping from default hyper optimizer and using basic `labels` method instead.\n", " warnings.warn(\n" ] } @@ -66,7 +66,7 @@ "from networkx.classes.graph import Graph\n", "from networkx.generators.lattice import hexagonal_lattice_graph\n", "\n", - "from qca.utils.utils import plot_histogram, EstimateMetaData\n", + "from qca.utils.utils import plot_histogram, QSPMetaData, TrotterizationMetaData \n", "from qca.utils.algo_utils import estimate_qsp, estimate_trotter\n", "from qca.utils.hamiltonian_utils import (nx_triangle_lattice, flatten_nx_graph,\n", " generate_square_hamiltonian, pyliqtr_hamiltonian_to_openfermion_qubit_operator,\n", @@ -95,7 +95,7 @@ "outputs": [ { "data": { - "image/png": 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", + "image/png": 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", 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" ] @@ -115,7 +115,7 @@ "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -135,7 +135,7 @@ "outputs": [ { "data": { - "image/png": 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", + "image/png": 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", "text/plain": [ "
" ] @@ -224,34 +224,43 @@ "metadata": {}, "outputs": [], "source": [ - "square_lattice_metadata = EstimateMetaData(\n", + "square_lattice_metadata = QSPMetaData(\n", " id=uid,\n", " name='square_lattice',\n", " category='scientific',\n", " size=f'lattice_size: {square_lattice_size}',\n", " task='Time Dependent Dynamics',\n", - " implementations=f'QSP, JT={evolution_time}, numsteps={numsteps}, required_precision={required_precision}',\n", + " implementation='QSP',\n", + " evolution_time=evolution_time,\n", + " nsteps=numsteps,\n", + " energy_precision=required_precision\n", ")\n", "uid += 1\n", "\n", - "triangle_lattice_metadata = EstimateMetaData(\n", + "triangle_lattice_metadata = QSPMetaData(\n", " id=uid,\n", - " name='triangle_lattice',\n", + " name='square_lattice',\n", " category='scientific',\n", - " size=f'lattice_size: {triangle_lattice_size}',\n", + " size=f'lattice_size: {square_lattice_size}',\n", " task='Time Dependent Dynamics',\n", - " implementations=f'QSP, JT={evolution_time}, numsteps={numsteps}, required_precision={required_precision}',\n", + " implementation='QSP',\n", + " evolution_time=evolution_time,\n", + " nsteps=numsteps,\n", + " energy_precision=required_precision\n", ")\n", "\n", "uid += 1\n", "\n", - "cubic_lattice_metadata = EstimateMetaData(\n", + "cubic_lattice_metadata = QSPMetaData(\n", " id=uid,\n", - " name='cube_lattice',\n", + " name='square_lattice',\n", " category='scientific',\n", - " size=f'lattice_size: {cubic_lattice_size}',\n", + " size=f'lattice_size: {square_lattice_size}',\n", " task='Time Dependent Dynamics',\n", - " implementations=f'QSP, JT={evolution_time}, numsteps={numsteps}, required_precision={required_precision}',\n", + " implementation='QSP',\n", + " evolution_time=evolution_time,\n", + " nsteps=numsteps,\n", + " energy_precision=required_precision\n", ")\n", "uid += 1" ] @@ -266,51 +275,51 @@ "output_type": "stream", "text": [ "Estimating Square\n", - "Time to generate high level QSP circuit: 0.08325587500075926 seconds\n", - " Time to decompose high level _PauliX circuit: 5.9250000049360096e-05 seconds \n", - " Time to transform decomposed _PauliX circuit to Clifford+T: 2.5875000574160367e-05 seconds\n", - " Time to decompose high level Rx circuit: 2.329099879716523e-05 seconds \n", - " Time to transform decomposed Rx circuit to Clifford+T: 0.008828415999232675 seconds\n", - " Time to decompose high level UnitaryBlockEncode circuit: 0.3315611669986538 seconds \n", - " Time to transform decomposed UnitaryBlockEncode circuit to Clifford+T: 1.3761872089999088 seconds\n", - " Time to decompose high level Ry circuit: 0.0021068749992991798 seconds \n", - " Time to transform decomposed Ry circuit to Clifford+T: 0.005764416999227251 seconds\n", - " Time to decompose high level _InverseCompositeGate circuit: 0.3549190419998922 seconds \n", - " Time to transform decomposed _InverseCompositeGate circuit to Clifford+T: 1.3856899999991583 seconds\n", - " Time to decompose high level Reflect circuit: 0.006387458000972401 seconds \n", - " Time to transform decomposed Reflect circuit to Clifford+T: 0.01555437500064727 seconds\n", + "Time to generate high level QSP circuit: 0.07294041698332876 seconds\n", + " Time to decompose high level _PauliX circuit: 4.199997056275606e-05 seconds \n", + " Time to transform decomposed _PauliX circuit to Clifford+T: 2.0875013433396816e-05 seconds\n", + " Time to decompose high level Rx circuit: 2.0250037778168917e-05 seconds \n", + " Time to transform decomposed Rx circuit to Clifford+T: 0.006910957978107035 seconds\n", + " Time to decompose high level UnitaryBlockEncode circuit: 0.3236018340103328 seconds \n", + " Time to transform decomposed UnitaryBlockEncode circuit to Clifford+T: 1.4018742089974694 seconds\n", + " Time to decompose high level Ry circuit: 0.0019690829794853926 seconds \n", + " Time to transform decomposed Ry circuit to Clifford+T: 0.005708707962185144 seconds\n", + " Time to decompose high level _InverseCompositeGate circuit: 0.25324670801637694 seconds \n", + " Time to transform decomposed _InverseCompositeGate circuit to Clifford+T: 1.350836208963301 seconds\n", + " Time to decompose high level Reflect circuit: 0.006207542028278112 seconds \n", + " Time to transform decomposed Reflect circuit to Clifford+T: 0.01463116699596867 seconds\n", "\n", "\n", "Estimating Triangle\n", - "Time to generate high level QSP circuit: 5.085025375001351 seconds\n", - " Time to decompose high level _PauliX circuit: 6.416600081138313e-05 seconds \n", - " Time to transform decomposed _PauliX circuit to Clifford+T: 2.4625000150990672e-05 seconds\n", - " Time to decompose high level Rx circuit: 2.8500000553322025e-05 seconds \n", - " Time to transform decomposed Rx circuit to Clifford+T: 0.007869625000239466 seconds\n", - " Time to decompose high level UnitaryBlockEncode circuit: 4.559109374999025 seconds \n", - " Time to transform decomposed UnitaryBlockEncode circuit to Clifford+T: 13.200007583000115 seconds\n", - " Time to decompose high level Ry circuit: 0.026712292001320748 seconds \n", - " Time to transform decomposed Ry circuit to Clifford+T: 0.005876041999727022 seconds\n", - " Time to decompose high level _InverseCompositeGate circuit: 4.882124958998247 seconds \n", - " Time to transform decomposed _InverseCompositeGate circuit to Clifford+T: 13.35177670899975 seconds\n", - " Time to decompose high level Reflect circuit: 0.035053540999797406 seconds \n", - " Time to transform decomposed Reflect circuit to Clifford+T: 0.019316957999762963 seconds\n", + "Time to generate high level QSP circuit: 4.435369957995135 seconds\n", + " Time to decompose high level _PauliX circuit: 6.42079976387322e-05 seconds \n", + " Time to transform decomposed _PauliX circuit to Clifford+T: 2.8958020266145468e-05 seconds\n", + " Time to decompose high level Rx circuit: 2.358300844207406e-05 seconds \n", + " Time to transform decomposed Rx circuit to Clifford+T: 0.006856874970253557 seconds\n", + " Time to decompose high level UnitaryBlockEncode circuit: 4.713378958986141 seconds \n", + " Time to transform decomposed UnitaryBlockEncode circuit to Clifford+T: 12.167330832977314 seconds\n", + " Time to decompose high level Ry circuit: 0.023170665954239666 seconds \n", + " Time to transform decomposed Ry circuit to Clifford+T: 0.005780374980531633 seconds\n", + " Time to decompose high level _InverseCompositeGate circuit: 4.896896124992054 seconds \n", + " Time to transform decomposed _InverseCompositeGate circuit to Clifford+T: 13.390764708048664 seconds\n", + " Time to decompose high level Reflect circuit: 0.03417441598139703 seconds \n", + " Time to transform decomposed Reflect circuit to Clifford+T: 0.01879554201150313 seconds\n", "\n", "\n", "Estimating Cube\n", - "Time to generate high level QSP circuit: 13.036277624998547 seconds\n", - " Time to decompose high level _PauliX circuit: 6.279099943640176e-05 seconds \n", - " Time to transform decomposed _PauliX circuit to Clifford+T: 2.204100019298494e-05 seconds\n", - " Time to decompose high level Rx circuit: 1.9832999896607362e-05 seconds \n", - " Time to transform decomposed Rx circuit to Clifford+T: 0.008222499998737476 seconds\n", - " Time to decompose high level UnitaryBlockEncode circuit: 6.269343207999555 seconds \n", - " Time to transform decomposed UnitaryBlockEncode circuit to Clifford+T: 19.10772524999993 seconds\n", - " Time to decompose high level Ry circuit: 0.04713808300039091 seconds \n", - " Time to transform decomposed Ry circuit to Clifford+T: 0.006180708000101731 seconds\n", - " Time to decompose high level _InverseCompositeGate circuit: 8.939842042000237 seconds \n", - " Time to transform decomposed _InverseCompositeGate circuit to Clifford+T: 32.164741540998875 seconds\n", - " Time to decompose high level Reflect circuit: 0.05777200000011362 seconds \n", - " Time to transform decomposed Reflect circuit to Clifford+T: 0.022344666998833418 seconds\n", + "Time to generate high level QSP circuit: 11.534532958990894 seconds\n", + " Time to decompose high level _PauliX circuit: 5.116598913446069e-05 seconds \n", + " Time to transform decomposed _PauliX circuit to Clifford+T: 2.0875013433396816e-05 seconds\n", + " Time to decompose high level Rx circuit: 2.31250305660069e-05 seconds \n", + " Time to transform decomposed Rx circuit to Clifford+T: 0.033716583042405546 seconds\n", + " Time to decompose high level UnitaryBlockEncode circuit: 9.297313249961007 seconds \n", + " Time to transform decomposed UnitaryBlockEncode circuit to Clifford+T: 18.542402041959576 seconds\n", + " Time to decompose high level Ry circuit: 0.039301375043578446 seconds \n", + " Time to transform decomposed Ry circuit to Clifford+T: 0.0058032089727930725 seconds\n", + " Time to decompose high level _InverseCompositeGate circuit: 6.9808499999926426 seconds \n", + " Time to transform decomposed _InverseCompositeGate circuit to Clifford+T: 18.716713583969977 seconds\n", + " Time to decompose high level Reflect circuit: 0.05238858296070248 seconds \n", + " Time to transform decomposed Reflect circuit to Clifford+T: 0.020020500000100583 seconds\n", "Finished estimating\n" ] } @@ -320,7 +329,7 @@ "qsp_circ_square = estimate_qsp(\n", " pyliqtr_hamiltonian=H_square,\n", " evolution_time=evolution_time,\n", - " numsteps=numsteps,\n", + " nsteps=numsteps,\n", " energy_precision=required_precision,\n", " outdir='QSP/square_circuits/',\n", " hamiltonian_name='square_qsp',\n", @@ -333,7 +342,7 @@ "qsp_circ_triangle = estimate_qsp(\n", " pyliqtr_hamiltonian=H_triangle,\n", " evolution_time=evolution_time,\n", - " numsteps=numsteps,\n", + " nsteps=numsteps,\n", " energy_precision=required_precision,\n", " metadata=triangle_lattice_metadata,\n", " outdir='QSP/triangle_circuits/',\n", @@ -346,7 +355,7 @@ "qsp_circ_cube = estimate_qsp(\n", " pyliqtr_hamiltonian=H_cube,\n", " evolution_time=evolution_time,\n", - " numsteps=numsteps,\n", + " nsteps=numsteps,\n", " energy_precision=required_precision,\n", " metadata=cubic_lattice_metadata,\n", " outdir='QSP/cube_circuits/',\n", @@ -372,7 +381,7 @@ "outputs": [ { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -439,19 +448,19 @@ "output_type": "stream", "text": [ "Estimating Kitaev\n", - "Time to generate high level QSP circuit: 17.22533520899924 seconds\n", - " Time to decompose high level _PauliX circuit: 0.000151833999552764 seconds \n", - " Time to transform decomposed _PauliX circuit to Clifford+T: 5.837500066263601e-05 seconds\n", - " Time to decompose high level Rx circuit: 8.316599996760488e-05 seconds \n", - " Time to transform decomposed Rx circuit to Clifford+T: 0.06194462500025111 seconds\n", - " Time to decompose high level UnitaryBlockEncode circuit: 6.88985566699921 seconds \n", - " Time to transform decomposed UnitaryBlockEncode circuit to Clifford+T: 29.980846917000235 seconds\n", - " Time to decompose high level Ry circuit: 0.02377604200046335 seconds \n", - " Time to transform decomposed Ry circuit to Clifford+T: 0.006591833998754737 seconds\n", - " Time to decompose high level _InverseCompositeGate circuit: 4.077777000000424 seconds \n", - " Time to transform decomposed _InverseCompositeGate circuit to Clifford+T: 21.787147625000216 seconds\n", - " Time to decompose high level Reflect circuit: 0.03148391699869535 seconds \n", - " Time to transform decomposed Reflect circuit to Clifford+T: 0.02030245800051489 seconds\n", + "Time to generate high level QSP circuit: 9.133365333022084 seconds\n", + " Time to decompose high level _PauliX circuit: 6.0999998822808266e-05 seconds \n", + " Time to transform decomposed _PauliX circuit to Clifford+T: 1.9458006136119366e-05 seconds\n", + " Time to decompose high level Rx circuit: 1.899997005239129e-05 seconds \n", + " Time to transform decomposed Rx circuit to Clifford+T: 0.00787954096449539 seconds\n", + " Time to decompose high level UnitaryBlockEncode circuit: 2.8740033750073053 seconds \n", + " Time to transform decomposed UnitaryBlockEncode circuit to Clifford+T: 12.072705541970208 seconds\n", + " Time to decompose high level Ry circuit: 0.019660042016766965 seconds \n", + " Time to transform decomposed Ry circuit to Clifford+T: 0.0059122079983353615 seconds\n", + " Time to decompose high level _InverseCompositeGate circuit: 3.7868810829822905 seconds \n", + " Time to transform decomposed _InverseCompositeGate circuit to Clifford+T: 13.98899787501432 seconds\n", + " Time to decompose high level Reflect circuit: 0.029673249984625727 seconds \n", + " Time to transform decomposed Reflect circuit to Clifford+T: 0.019305041001643986 seconds\n", "Finished Estimating\n" ] } @@ -467,20 +476,23 @@ "\n", "H_kitaev = pyH(kitaev_hamiltonian)\n", "\n", - "kitaev_metadata = EstimateMetaData(\n", + "kitaev_metadata = QSPMetaData(\n", " id=uid,\n", " name='Kitaev_qsp',\n", " category='scientific',\n", " size=f'lattice_size: {lattice_size_kitaev}',\n", " task='Time Dependent Dynamics',\n", - " implementations=f'QSP, JT={evolution_time}, numsteps={numsteps}, required_precision={required_precision}',\n", + " implementation='QSP',\n", + " evolution_time=evolution_time,\n", + " nsteps=numsteps,\n", + " energy_precision=required_precision\n", ")\n", "uid +=1 \n", "print('Estimating Kitaev', flush=True)\n", "qsp_circ_kitaev = estimate_qsp(\n", " pyliqtr_hamiltonian=H_kitaev,\n", " evolution_time=evolution_time,\n", - " numsteps=numsteps,\n", + " nsteps=numsteps,\n", " energy_precision=required_precision,\n", " metadata=kitaev_metadata,\n", " outdir='QSP/kitaev_circuits/',\n", @@ -514,7 +526,7 @@ "outputs": [ { "data": { - "image/png": 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", + "image/png": 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", "text/plain": [ "
" ] @@ -542,19 +554,19 @@ "output_type": "stream", "text": [ "Estimating Directional Triangle\n", - "Time to generate high level QSP circuit: 4.829019250000783 seconds\n", - " Time to decompose high level _PauliX circuit: 6.949999988137279e-05 seconds \n", - " Time to transform decomposed _PauliX circuit to Clifford+T: 2.637499892443884e-05 seconds\n", - " Time to decompose high level Rx circuit: 2.8750000637955964e-05 seconds \n", - " Time to transform decomposed Rx circuit to Clifford+T: 0.007816750001438777 seconds\n", - " Time to decompose high level UnitaryBlockEncode circuit: 2.616756790999716 seconds \n", - " Time to transform decomposed UnitaryBlockEncode circuit to Clifford+T: 20.199338749998788 seconds\n", - " Time to decompose high level Ry circuit: 0.02131474999987404 seconds \n", - " Time to transform decomposed Ry circuit to Clifford+T: 0.00591987500047253 seconds\n", - " Time to decompose high level _InverseCompositeGate circuit: 3.336558957998932 seconds \n", - " Time to transform decomposed _InverseCompositeGate circuit to Clifford+T: 15.022351999999955 seconds\n", - " Time to decompose high level Reflect circuit: 0.15153470900077082 seconds \n", - " Time to transform decomposed Reflect circuit to Clifford+T: 0.056581000000733184 seconds\n", + "Time to generate high level QSP circuit: 4.235135082970373 seconds\n", + " Time to decompose high level _PauliX circuit: 6.212497828528285e-05 seconds \n", + " Time to transform decomposed _PauliX circuit to Clifford+T: 2.120796125382185e-05 seconds\n", + " Time to decompose high level Rx circuit: 2.0875013433396816e-05 seconds \n", + " Time to transform decomposed Rx circuit to Clifford+T: 0.00715437502367422 seconds\n", + " Time to decompose high level UnitaryBlockEncode circuit: 2.4512442080304027 seconds \n", + " Time to transform decomposed UnitaryBlockEncode circuit to Clifford+T: 17.03530916699674 seconds\n", + " Time to decompose high level Ry circuit: 0.0189153749961406 seconds \n", + " Time to transform decomposed Ry circuit to Clifford+T: 0.00599454203620553 seconds\n", + " Time to decompose high level _InverseCompositeGate circuit: 4.911995624948759 seconds \n", + " Time to transform decomposed _InverseCompositeGate circuit to Clifford+T: 14.278082708013244 seconds\n", + " Time to decompose high level Reflect circuit: 0.028568209032528102 seconds \n", + " Time to transform decomposed Reflect circuit to Clifford+T: 0.018655833031516522 seconds\n", "Finished Estimating\n" ] } @@ -569,20 +581,23 @@ "required_precision = 1e-16\n", "H_directional_triangle = pyH(directional_triangle_hamiltonian)\n", "\n", - "directional_trangle_metadata = EstimateMetaData(\n", + "directional_trangle_metadata = QSPMetaData(\n", " id=uid,\n", " name='directional_triangle_qsp',\n", " category='scientific',\n", " size=f'lattice_size: {lattice_size_directional_triangle}',\n", " task='Time Dependent Dynamics',\n", - " implementations=f'QSP, JT={evolution_time}, numsteps={numsteps}, required_precision={required_precision}',\n", + " implementation='QSP',\n", + " evolution_time=evolution_time,\n", + " nsteps=numsteps,\n", + " energy_precision=required_precision\n", ")\n", "uid += 1\n", "print('Estimating Directional Triangle', flush=True)\n", "qsp_circ_directional_triangle = estimate_qsp(\n", " pyliqtr_hamiltonian=H_directional_triangle,\n", " evolution_time=evolution_time,\n", - " numsteps=numsteps,\n", + " nsteps=numsteps,\n", " energy_precision=required_precision,\n", " metadata=directional_trangle_metadata,\n", " outdir='QSP/directional_triangle_circuits/',\n", @@ -602,7 +617,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 17, "metadata": {}, "outputs": [], "source": [ @@ -613,53 +628,83 @@ "openfermion_hamiltonian_kitaev = pyliqtr_hamiltonian_to_openfermion_qubit_operator(H_kitaev)\n", "openfermion_hamiltonian_directional_triangle = pyliqtr_hamiltonian_to_openfermion_qubit_operator(H_directional_triangle)\n", "\n", - "trotter_square_metadata = EstimateMetaData(\n", + "#Explicitly set the trotter order to 2, is set to 2 by default by estimate.\n", + "\n", + "# defining precision required for the trotterized circuit\n", + "energy_precision = 1e-6\n", + "evolution_time=1000\n", + "\n", + "trotter_order=2\n", + "\n", + "extrapolate=True\n", + "\n", + "trotter_square_metadata = TrotterizationMetaData(\n", " id=uid,\n", " name='square_lattice_trotter',\n", " category='scientific',\n", " size=f'lattice_size: {square_lattice_size}',\n", " task='Time Dependent Dynamics',\n", - " implementations=f'trotterization, JT={evolution_time}, numsteps={numsteps}, required_precision={required_precision}',\n", + " implementation='trotterization',\n", + " evolution_time=evolution_time,\n", + " trotter_order= 2,\n", + " is_extrapolated=extrapolate,\n", + " energy_precision=required_precision,\n", ")\n", "uid += 1\n", "\n", - "trotter_triangle_metadata = EstimateMetaData(\n", + "trotter_triangle_metadata = TrotterizationMetaData(\n", " id=uid,\n", - " name='triangle_lattice_trotter',\n", + " name='square_lattice_trotter',\n", " category='scientific',\n", - " size=f'lattice_size: {triangle_lattice_size}',\n", + " size=f'lattice_size: {square_lattice_size}',\n", " task='Time Dependent Dynamics',\n", - " implementations=f'trotterization, JT={evolution_time}, numsteps={numsteps}, required_precision={required_precision}',\n", + " implementation='trotterization',\n", + " evolution_time=evolution_time,\n", + " trotter_order= 2,\n", + " is_extrapolated=extrapolate,\n", + " energy_precision=required_precision,\n", ")\n", "uid += 1\n", "\n", - "trotter_cubic_metadata = EstimateMetaData(\n", + "trotter_cubic_metadata = TrotterizationMetaData(\n", " id=uid,\n", - " name='triangle_lattice_trotter',\n", + " name='square_lattice_trotter',\n", " category='scientific',\n", - " size=f'lattice_size: {cubic_lattice_size}',\n", + " size=f'lattice_size: {square_lattice_size}',\n", " task='Time Dependent Dynamics',\n", - " implementations=f'trotterization, JT={evolution_time}, numsteps={numsteps}, required_precision={required_precision}',\n", + " implementation='trotterization',\n", + " evolution_time=evolution_time,\n", + " trotter_order= 2,\n", + " is_extrapolated=extrapolate,\n", + " energy_precision=required_precision,\n", ")\n", "uid += 1\n", "\n", - "trotter_kitaev_metadata = EstimateMetaData(\n", + "trotter_kitaev_metadata = TrotterizationMetaData(\n", " id=uid,\n", - " name='kitaev_lattice_trotter',\n", + " name='square_lattice_trotter',\n", " category='scientific',\n", - " size=f'lattice_size: {lattice_size_kitaev}',\n", + " size=f'lattice_size: {square_lattice_size}',\n", " task='Time Dependent Dynamics',\n", - " implementations=f'trotterization, JT={evolution_time}, numsteps={numsteps}, required_precision={required_precision}',\n", + " implementation='trotterization',\n", + " evolution_time=evolution_time,\n", + " trotter_order= 2,\n", + " is_extrapolated=extrapolate,\n", + " energy_precision=required_precision,\n", ")\n", "uid += 1\n", "\n", - "trotter_directional_triangle_metadata = EstimateMetaData(\n", + "trotter_directional_triangle_metadata = TrotterizationMetaData(\n", " id=uid,\n", - " name='directional_triangle_lattice_trotter',\n", + " name='square_lattice_trotter',\n", " category='scientific',\n", - " size=f'lattice_size: {lattice_size_directional_triangle}',\n", + " size=f'lattice_size: {square_lattice_size}',\n", " task='Time Dependent Dynamics',\n", - " implementations=f'trotterization, JT={evolution_time}, numsteps={numsteps}, required_precision={required_precision}',\n", + " implementation='trotterization',\n", + " evolution_time=evolution_time,\n", + " trotter_order= 2,\n", + " is_extrapolated=extrapolate,\n", + " energy_precision=required_precision,\n", ")\n", "uid += 1\n" ] @@ -672,17 +717,6 @@ "Trotterizing the Hamiltonians and writing estimates to files" ] }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": {}, - "outputs": [], - "source": [ - "# defining precision required for the trotterized circuit\n", - "energy_precision = 1e-6\n", - "evolution_time=1000" - ] - }, { "cell_type": "code", "execution_count": 18, @@ -693,30 +727,30 @@ "output_type": "stream", "text": [ "Estimating Square\n", - "Time to estimate number of trotter steps required (5366564): 0.039078792000509566 seconds\n", - "Time to find term ordering: 0.00381958399884752 seconds\n", - "Time to generate trotter circuit from openfermion: 2.6249999791616574e-06 seconds\n", - "Time to generate a clifford + T circuit from trotter circuit: 2.6665572080000857 seconds\n", + "Time to estimate number of trotter steps required (5366564): 0.02420575002906844 seconds\n", + "Time to find term ordering: 0.001630583021324128 seconds\n", + "Time to generate trotter circuit from openfermion: 1.2500095181167126e-06 seconds\n", + "Time to generate a clifford + T circuit from trotter circuit: 3.175797624979168 seconds\n", "Estimating Triangle\n", - "Time to estimate number of trotter steps required (21707142): 2.7135432499999297 seconds\n", - "Time to find term ordering: 0.024939625000115484 seconds\n", - "Time to generate trotter circuit from openfermion: 1.4589986676583067e-06 seconds\n", - "Time to generate a clifford + T circuit from trotter circuit: 62.87029233300018 seconds\n", + "Time to estimate number of trotter steps required (21707142): 2.472716875025071 seconds\n", + "Time to find term ordering: 0.02231966599356383 seconds\n", + "Time to generate trotter circuit from openfermion: 1.249951310455799e-06 seconds\n", + "Time to generate a clifford + T circuit from trotter circuit: 43.7863163750153 seconds\n", "Estimating Cube\n", - "Time to estimate number of trotter steps required (27573901): 7.322590750000018 seconds\n", - "Time to find term ordering: 0.040885958000217215 seconds\n", - "Time to generate trotter circuit from openfermion: 1.7910006135934964e-06 seconds\n", - "Time to generate a clifford + T circuit from trotter circuit: 98.80615391699939 seconds\n", + "Time to estimate number of trotter steps required (27573901): 6.365963499993086 seconds\n", + "Time to find term ordering: 0.03880191600183025 seconds\n", + "Time to generate trotter circuit from openfermion: 1.3750395737588406e-06 seconds\n", + "Time to generate a clifford + T circuit from trotter circuit: 69.69336341699818 seconds\n", "Estimating Kitaev\n", - "Time to estimate number of trotter steps required (222782406): 4.533966249999139 seconds\n", - "Time to find term ordering: 0.16492637500050478 seconds\n", - "Time to generate trotter circuit from openfermion: 1.2090004020137712e-06 seconds\n", - "Time to generate a clifford + T circuit from trotter circuit: 43.767634959000134 seconds\n", + "Time to estimate number of trotter steps required (222782406): 1.8363965000025928 seconds\n", + "Time to find term ordering: 0.01799762499285862 seconds\n", + "Time to generate trotter circuit from openfermion: 1.2500095181167126e-06 seconds\n", + "Time to generate a clifford + T circuit from trotter circuit: 36.06559366598958 seconds\n", "Estimating Directional Triangle\n", - "Time to estimate number of trotter steps required (433303589): 4.0636968329999945 seconds\n", - "Time to find term ordering: 0.13614829200014356 seconds\n", - "Time to generate trotter circuit from openfermion: 9.625000529922545e-06 seconds\n", - "Time to generate a clifford + T circuit from trotter circuit: 51.84814395899957 seconds\n", + "Time to estimate number of trotter steps required (433303589): 1.6750391669920646 seconds\n", + "Time to find term ordering: 0.023808708996511996 seconds\n", + "Time to generate trotter circuit from openfermion: 1.2080417945981026e-06 seconds\n", + "Time to generate a clifford + T circuit from trotter circuit: 42.000205042015295 seconds\n", "Finished with estimates\n" ] } @@ -800,7 +834,7 @@ "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -825,7 +859,7 @@ "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -850,7 +884,7 @@ "outputs": [ { "data": { - "image/png": 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", + "image/png": 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", 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" ] @@ -875,7 +909,7 @@ "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -900,7 +934,7 @@ "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -928,7 +962,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3 (ipykernel)", + "display_name": "qc-apps", "language": "python", "name": "python3" }, @@ -942,7 +976,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.12.0" + "version": "3.11.10" } }, "nbformat": 4, diff --git a/notebooks/PhotosynthesisExample.ipynb b/notebooks/PhotosynthesisExample.ipynb index ca9936f..5af087d 100644 --- a/notebooks/PhotosynthesisExample.ipynb +++ b/notebooks/PhotosynthesisExample.ipynb @@ -50,7 +50,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "/Users/jonhas/anaconda3/envs/other/lib/python3.12/site-packages/cotengra/hyperoptimizers/hyper.py:33: UserWarning: Couldn't import `kahypar` - skipping from default hyper optimizer and using basic `labels` method instead.\n", + "/Users/gsgrattan/.conda/envs/qc-apps/lib/python3.11/site-packages/cotengra/hyperoptimizers/hyper.py:33: UserWarning: Couldn't import `kahypar` - skipping from default hyper optimizer and using basic `labels` method instead.\n", " warnings.warn(\n" ] } @@ -66,7 +66,7 @@ "from openfermion.chem import MolecularData\n", "from pyLIQTR.PhaseEstimation.pe import PhaseEstimation\n", "from openfermion.ops.representations import InteractionOperator\n", - "from qca.utils.utils import extract_number, gen_resource_estimate, EstimateMetaData\n", + "from qca.utils.utils import extract_number, gen_resource_estimate, GSEEMetaData\n", "from qca.utils.algo_utils import gsee_resource_estimation" ] }, @@ -225,7 +225,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Time to perform a HF calculation on molecule 0 : 75.90567537499919\n", + "Time to perform a HF calculation on molecule 0 : 44.94567812496098\n", "Number of orbitals : 100\n", "Number of electrons : 148\n", "Number of qubits : 200\n", @@ -237,9 +237,9 @@ "In the Molecular Orbital Basis: we have 18 qubits\n", "In the Molecular Orbital Basis: we have 13 qubits occupied\n", "In the Molecular Orbital Basis: we have 5 qubits unoccupied\n", - "Time to generate a molecular hamiltonian for molecule 0 : 75.91670262500156\n", + "Time to generate a molecular hamiltonian for molecule 0 : 44.95591650001006\n", "\n", - "Time to perform a HF calculation on molecule 1 : 87.17327162500078\n", + "Time to perform a HF calculation on molecule 1 : 59.59993424999993\n", "Number of orbitals : 99\n", "Number of electrons : 147\n", "Number of qubits : 198\n", @@ -251,9 +251,9 @@ "In the Molecular Orbital Basis: we have 18 qubits\n", "In the Molecular Orbital Basis: we have 13 qubits occupied\n", "In the Molecular Orbital Basis: we have 5 qubits unoccupied\n", - "Time to generate a molecular hamiltonian for molecule 1 : 87.19545470900084\n", + "Time to generate a molecular hamiltonian for molecule 1 : 59.62234137498308\n", "\n", - "Time to perform a HF calculation on molecule 2 : 88.68229533399972\n", + "Time to perform a HF calculation on molecule 2 : 56.79980720899766\n", "Number of orbitals : 98\n", "Number of electrons : 146\n", "Number of qubits : 196\n", @@ -265,9 +265,9 @@ "In the Molecular Orbital Basis: we have 18 qubits\n", "In the Molecular Orbital Basis: we have 13 qubits occupied\n", "In the Molecular Orbital Basis: we have 5 qubits unoccupied\n", - "Time to generate a molecular hamiltonian for molecule 2 : 88.70473058300013\n", + "Time to generate a molecular hamiltonian for molecule 2 : 56.82168937503593\n", "\n", - "Time to perform a HF calculation on molecule 3 : 84.60689258400089\n", + "Time to perform a HF calculation on molecule 3 : 54.94790525001008\n", "Number of orbitals : 97\n", "Number of electrons : 145\n", "Number of qubits : 194\n", @@ -279,9 +279,9 @@ "In the Molecular Orbital Basis: we have 18 qubits\n", "In the Molecular Orbital Basis: we have 13 qubits occupied\n", "In the Molecular Orbital Basis: we have 5 qubits unoccupied\n", - "Time to generate a molecular hamiltonian for molecule 3 : 84.6291376249992\n", + "Time to generate a molecular hamiltonian for molecule 3 : 54.969166708004195\n", "\n", - "Time to perform a HF calculation on molecule 4 : 83.06734229199901\n", + "Time to perform a HF calculation on molecule 4 : 55.622391791956034\n", "Number of orbitals : 97\n", "Number of electrons : 145\n", "Number of qubits : 194\n", @@ -293,9 +293,9 @@ "In the Molecular Orbital Basis: we have 18 qubits\n", "In the Molecular Orbital Basis: we have 13 qubits occupied\n", "In the Molecular Orbital Basis: we have 5 qubits unoccupied\n", - "Time to generate a molecular hamiltonian for molecule 4 : 83.08867879200079\n", + "Time to generate a molecular hamiltonian for molecule 4 : 55.64403199998196\n", "\n", - "Time to perform a HF calculation on molecule 5 : 85.18758354199963\n", + "Time to perform a HF calculation on molecule 5 : 54.11503083398566\n", "Number of orbitals : 97\n", "Number of electrons : 145\n", "Number of qubits : 194\n", @@ -307,9 +307,9 @@ "In the Molecular Orbital Basis: we have 18 qubits\n", "In the Molecular Orbital Basis: we have 13 qubits occupied\n", "In the Molecular Orbital Basis: we have 5 qubits unoccupied\n", - "Time to generate a molecular hamiltonian for molecule 5 : 85.20938883300005\n", + "Time to generate a molecular hamiltonian for molecule 5 : 54.136136332992464\n", "\n", - "Time to perform a HF calculation on molecule 6 : 95.03422583299835\n", + "Time to perform a HF calculation on molecule 6 : 66.90098125004442\n", "Number of orbitals : 104\n", "Number of electrons : 155\n", "Number of qubits : 208\n", @@ -321,9 +321,9 @@ "In the Molecular Orbital Basis: we have 18 qubits\n", "In the Molecular Orbital Basis: we have 13 qubits occupied\n", "In the Molecular Orbital Basis: we have 5 qubits unoccupied\n", - "Time to generate a molecular hamiltonian for molecule 6 : 95.05870970799879\n", + "Time to generate a molecular hamiltonian for molecule 6 : 66.92277670901967\n", "\n", - "Time to perform a HF calculation on molecule 7 : 80.24046758400073\n", + "Time to perform a HF calculation on molecule 7 : 51.68452154198894\n", "Number of orbitals : 94\n", "Number of electrons : 139\n", "Number of qubits : 188\n", @@ -335,9 +335,9 @@ "In the Molecular Orbital Basis: we have 16 qubits\n", "In the Molecular Orbital Basis: we have 12 qubits occupied\n", "In the Molecular Orbital Basis: we have 4 qubits unoccupied\n", - "Time to generate a molecular hamiltonian for molecule 7 : 80.26959662500121\n", + "Time to generate a molecular hamiltonian for molecule 7 : 51.706565667001996\n", "\n", - "Time to perform a HF calculation on molecule 8 : 94.25143608399958\n", + "Time to perform a HF calculation on molecule 8 : 61.47438433399657\n", "Number of orbitals : 101\n", "Number of electrons : 149\n", "Number of qubits : 202\n", @@ -349,7 +349,7 @@ "In the Molecular Orbital Basis: we have 18 qubits\n", "In the Molecular Orbital Basis: we have 13 qubits occupied\n", "In the Molecular Orbital Basis: we have 5 qubits unoccupied\n", - "Time to generate a molecular hamiltonian for molecule 8 : 94.27698975000021\n", + "Time to generate a molecular hamiltonian for molecule 8 : 61.49484970798949\n", "\n" ] } @@ -542,139 +542,139 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 10, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Time to generate circuit for GSEE: 7.912499859230593e-05 seconds\n", - " Time to decompose high level HPowGate circuit: 0.0004527080000116257 seconds \n", - " Time to transform decomposed HPowGate circuit to Clifford+T: 0.0012273749998712447 seconds\n", - " Time to decompose high level IdentityGate circuit: 1.4250001186155714e-05 seconds \n", - " Time to transform decomposed IdentityGate circuit to Clifford+T: 4.37500057159923e-06 seconds\n", - " Time to decompose high level _PauliX circuit: 3.2250000003841706e-05 seconds \n", - " Time to transform decomposed _PauliX circuit to Clifford+T: 1.8374999854131602e-05 seconds\n", - " Time to decompose high level PhaseOffset circuit: 9.675000001152512e-05 seconds \n", - " Time to transform decomposed PhaseOffset circuit to Clifford+T: 9.341700024378952e-05 seconds\n", - " Time to decompose high level Trotter_Unitary circuit: 37.72577670800092 seconds \n", - " Time to transform decomposed Trotter_Unitary circuit to Clifford+T: 217.44230333400083 seconds\n", - " Time to decompose high level MeasurementGate circuit: 0.3348573330004001 seconds \n", - " Time to transform decomposed MeasurementGate circuit to Clifford+T: 0.00021574999846052378 seconds\n", - "Time to estimate Co2O9H12_step(0): 464.8170198750013\n", - "Time to generate circuit for GSEE: 0.00023704200066276826 seconds\n", - " Time to decompose high level HPowGate circuit: 0.00033408299896109384 seconds \n", - " Time to transform decomposed HPowGate circuit to Clifford+T: 0.0004187499998806743 seconds\n", - " Time to decompose high level IdentityGate circuit: 1.6125000911415555e-05 seconds \n", - " Time to transform decomposed IdentityGate circuit to Clifford+T: 4.833000275539234e-06 seconds\n", - " Time to decompose high level _PauliX circuit: 3.087500044784974e-05 seconds \n", - " Time to transform decomposed _PauliX circuit to Clifford+T: 1.633300053072162e-05 seconds\n", - " Time to decompose high level PhaseOffset circuit: 0.00011954199908359442 seconds \n", - " Time to transform decomposed PhaseOffset circuit to Clifford+T: 0.00012674999925366137 seconds\n", - " Time to decompose high level Trotter_Unitary circuit: 33.263247625000076 seconds \n", - " Time to transform decomposed Trotter_Unitary circuit to Clifford+T: 207.58128083300107 seconds\n", - " Time to decompose high level MeasurementGate circuit: 0.13029879199893912 seconds \n", - " Time to transform decomposed MeasurementGate circuit to Clifford+T: 0.00010170799941988662 seconds\n", - "Time to estimate Co2O9H12_step(1): 412.55863679200047\n", - "Time to generate circuit for GSEE: 5.899999996472616e-05 seconds\n", - " Time to decompose high level HPowGate circuit: 0.00010620899956848007 seconds \n", - " Time to transform decomposed HPowGate circuit to Clifford+T: 0.0002892079992307117 seconds\n", - " Time to decompose high level IdentityGate circuit: 1.4125000234344043e-05 seconds \n", - " Time to transform decomposed IdentityGate circuit to Clifford+T: 3.832999937003478e-06 seconds\n", - " Time to decompose high level _PauliX circuit: 2.3874999897088856e-05 seconds \n", - " Time to transform decomposed _PauliX circuit to Clifford+T: 1.5749999874969944e-05 seconds\n", - " Time to decompose high level PhaseOffset circuit: 6.775000110792462e-05 seconds \n", - " Time to transform decomposed PhaseOffset circuit to Clifford+T: 7.991699931153562e-05 seconds\n", - " Time to decompose high level Trotter_Unitary circuit: 32.69873874999939 seconds \n", - " Time to transform decomposed Trotter_Unitary circuit to Clifford+T: 209.44834741699924 seconds\n", - " Time to decompose high level MeasurementGate circuit: 0.11836295800094376 seconds \n", - " Time to transform decomposed MeasurementGate circuit to Clifford+T: 9.654200039221905e-05 seconds\n", - "Time to estimate Co2O9H12_step(2): 422.24999545899846\n", - "Time to generate circuit for GSEE: 5.2584000513888896e-05 seconds\n", - " Time to decompose high level HPowGate circuit: 8.887500007404014e-05 seconds \n", - " Time to transform decomposed HPowGate circuit to Clifford+T: 0.00021462499898916576 seconds\n", - " Time to decompose high level IdentityGate circuit: 1.1625001206994057e-05 seconds \n", - " Time to transform decomposed IdentityGate circuit to Clifford+T: 3.3750002330634743e-06 seconds\n", - " Time to decompose high level _PauliX circuit: 2.208399928349536e-05 seconds \n", - " Time to transform decomposed _PauliX circuit to Clifford+T: 1.4416000340133905e-05 seconds\n", - " Time to decompose high level PhaseOffset circuit: 6.470800144597888e-05 seconds \n", - " Time to transform decomposed PhaseOffset circuit to Clifford+T: 7.5459000072442e-05 seconds\n", - " Time to decompose high level Trotter_Unitary circuit: 32.1086763330004 seconds \n", - " Time to transform decomposed Trotter_Unitary circuit to Clifford+T: 184.38333541700013 seconds\n", - " Time to decompose high level MeasurementGate circuit: 0.11966841699904762 seconds \n", - " Time to transform decomposed MeasurementGate circuit to Clifford+T: 0.00010141700113308616 seconds\n", - "Time to estimate Co2O9H12_step(3): 381.12187420900045\n", - "Time to generate circuit for GSEE: 5.149999924469739e-05 seconds\n", - " Time to decompose high level HPowGate circuit: 8.616599916422274e-05 seconds \n", - " Time to transform decomposed HPowGate circuit to Clifford+T: 0.00021374999960244168 seconds\n", - " Time to decompose high level IdentityGate circuit: 1.158399936684873e-05 seconds \n", - " Time to transform decomposed IdentityGate circuit to Clifford+T: 3.416000254219398e-06 seconds\n", - " Time to decompose high level _PauliX circuit: 2.3167000108514912e-05 seconds \n", - " Time to transform decomposed _PauliX circuit to Clifford+T: 1.5042000086396001e-05 seconds\n", - " Time to decompose high level PhaseOffset circuit: 6.345800102280919e-05 seconds \n", - " Time to transform decomposed PhaseOffset circuit to Clifford+T: 7.974999971338548e-05 seconds\n", - " Time to decompose high level Trotter_Unitary circuit: 32.35671291700055 seconds \n", - " Time to transform decomposed Trotter_Unitary circuit to Clifford+T: 173.23462958300115 seconds\n", - " Time to decompose high level MeasurementGate circuit: 0.11805583299974387 seconds \n", - " Time to transform decomposed MeasurementGate circuit to Clifford+T: 9.462499838264193e-05 seconds\n", - "Time to estimate Co2O9H12_step(4): 356.725256791\n", - "Time to generate circuit for GSEE: 5.599999894911889e-05 seconds\n", - " Time to decompose high level HPowGate circuit: 0.00010791699969558977 seconds \n", - " Time to transform decomposed HPowGate circuit to Clifford+T: 0.00024891700013540685 seconds\n", - " Time to decompose high level IdentityGate circuit: 1.2333999620750546e-05 seconds \n", - " Time to transform decomposed IdentityGate circuit to Clifford+T: 3.832999937003478e-06 seconds\n", - " Time to decompose high level _PauliX circuit: 2.5667000954854302e-05 seconds \n", - " Time to transform decomposed _PauliX circuit to Clifford+T: 1.670800156716723e-05 seconds\n", - " Time to decompose high level PhaseOffset circuit: 7.058299888740294e-05 seconds \n", - " Time to transform decomposed PhaseOffset circuit to Clifford+T: 8.799999886832666e-05 seconds\n", - " Time to decompose high level Trotter_Unitary circuit: 34.80839908300004 seconds \n", - " Time to transform decomposed Trotter_Unitary circuit to Clifford+T: 208.51571825000065 seconds\n", - " Time to decompose high level MeasurementGate circuit: 0.1333047500011162 seconds \n", - " Time to transform decomposed MeasurementGate circuit to Clifford+T: 0.00010874999861698598 seconds\n", - "Time to estimate Co2O9H12_step(5): 413.82990058299947\n", - "Time to generate circuit for GSEE: 5.9250000049360096e-05 seconds\n", - " Time to decompose high level HPowGate circuit: 8.120799975586124e-05 seconds \n", - " Time to transform decomposed HPowGate circuit to Clifford+T: 0.00022841700047138147 seconds\n", - " Time to decompose high level IdentityGate circuit: 1.4541999917128123e-05 seconds \n", - " Time to transform decomposed IdentityGate circuit to Clifford+T: 4.999999873689376e-06 seconds\n", - " Time to decompose high level _PauliX circuit: 2.537500040489249e-05 seconds \n", - " Time to transform decomposed _PauliX circuit to Clifford+T: 3.487499998300336e-05 seconds\n", - " Time to decompose high level PhaseOffset circuit: 7.112499952199869e-05 seconds \n", - " Time to transform decomposed PhaseOffset circuit to Clifford+T: 9.049999971466605e-05 seconds\n", - " Time to decompose high level Trotter_Unitary circuit: 32.07418387500002 seconds \n", - " Time to transform decomposed Trotter_Unitary circuit to Clifford+T: 175.00376704100017 seconds\n", - " Time to decompose high level MeasurementGate circuit: 0.1182163749999745 seconds \n", - " Time to transform decomposed MeasurementGate circuit to Clifford+T: 9.379100083606318e-05 seconds\n", - "Time to estimate Co2O9H12_step(6): 366.9860755000009\n", - "Time to generate circuit for GSEE: 5.46669998584548e-05 seconds\n", - " Time to decompose high level HPowGate circuit: 8.908399831852876e-05 seconds \n", - " Time to transform decomposed HPowGate circuit to Clifford+T: 0.00023762500131851994 seconds\n", - " Time to decompose high level IdentityGate circuit: 2.4791999749140814e-05 seconds \n", - " Time to transform decomposed IdentityGate circuit to Clifford+T: 4.666000677389093e-06 seconds\n", - " Time to decompose high level _PauliX circuit: 3.5832999856211245e-05 seconds \n", - " Time to transform decomposed _PauliX circuit to Clifford+T: 1.8167000234825537e-05 seconds\n", - " Time to decompose high level PhaseOffset circuit: 7.324999933189247e-05 seconds \n", - " Time to transform decomposed PhaseOffset circuit to Clifford+T: 0.00010204099999100436 seconds\n", - " Time to decompose high level Trotter_Unitary circuit: 18.869881583001188 seconds \n", - " Time to transform decomposed Trotter_Unitary circuit to Clifford+T: 122.0832411249994 seconds\n", - " Time to decompose high level MeasurementGate circuit: 0.06880479200117406 seconds \n", - " Time to transform decomposed MeasurementGate circuit to Clifford+T: 8.270800026366487e-05 seconds\n", - "Time to estimate Co2O9H12_step(7): 244.88016091700047\n", - "Time to generate circuit for GSEE: 5.7458000810584053e-05 seconds\n", - " Time to decompose high level HPowGate circuit: 9.345800026494544e-05 seconds \n", - " Time to transform decomposed HPowGate circuit to Clifford+T: 0.0002251250007248018 seconds\n", - " Time to decompose high level IdentityGate circuit: 1.1833000826300122e-05 seconds \n", - " Time to transform decomposed IdentityGate circuit to Clifford+T: 3.6250003176974133e-06 seconds\n", - " Time to decompose high level _PauliX circuit: 2.3333999706665054e-05 seconds \n", - " Time to transform decomposed _PauliX circuit to Clifford+T: 2.0041999960085377e-05 seconds\n", - " Time to decompose high level PhaseOffset circuit: 6.504200064227916e-05 seconds \n", - " Time to transform decomposed PhaseOffset circuit to Clifford+T: 9.308299922849983e-05 seconds\n", - " Time to decompose high level Trotter_Unitary circuit: 37.99790083300104 seconds \n", - " Time to transform decomposed Trotter_Unitary circuit to Clifford+T: 180.73486191700067 seconds\n", - " Time to decompose high level MeasurementGate circuit: 0.17056837500058464 seconds \n", - " Time to transform decomposed MeasurementGate circuit to Clifford+T: 0.0001418330011802027 seconds\n", - "Time to estimate Co2O9H12_step(8): 374.57792529200015\n" + "Time to generate circuit for GSEE: 0.0001236249809153378 seconds\n", + " Time to decompose high level HPowGate circuit: 0.00017012498574331403 seconds \n", + " Time to transform decomposed HPowGate circuit to Clifford+T: 0.00043766602175310254 seconds\n", + " Time to decompose high level IdentityGate circuit: 1.8667022231966257e-05 seconds \n", + " Time to transform decomposed IdentityGate circuit to Clifford+T: 2.2082997020334005e-05 seconds\n", + " Time to decompose high level _PauliX circuit: 3.9832957554608583e-05 seconds \n", + " Time to transform decomposed _PauliX circuit to Clifford+T: 2.216600114479661e-05 seconds\n", + " Time to decompose high level PhaseOffset circuit: 8.141703438013792e-05 seconds \n", + " Time to transform decomposed PhaseOffset circuit to Clifford+T: 0.00010900001507252455 seconds\n", + " Time to decompose high level Trotter_Unitary circuit: 33.39688883302733 seconds \n", + " Time to transform decomposed Trotter_Unitary circuit to Clifford+T: 191.66754699999 seconds\n", + " Time to decompose high level MeasurementGate circuit: 0.10163079196354374 seconds \n", + " Time to transform decomposed MeasurementGate circuit to Clifford+T: 0.00010099995415657759 seconds\n", + "Time to estimate Co2O9H12_step(0): 385.569837292016\n", + "Time to generate circuit for GSEE: 4.274997627362609e-05 seconds\n", + " Time to decompose high level HPowGate circuit: 0.00011383299715816975 seconds \n", + " Time to transform decomposed HPowGate circuit to Clifford+T: 0.00039770803414285183 seconds\n", + " Time to decompose high level IdentityGate circuit: 1.4666002243757248e-05 seconds \n", + " Time to transform decomposed IdentityGate circuit to Clifford+T: 4.582980182021856e-06 seconds\n", + " Time to decompose high level _PauliX circuit: 2.4040986318141222e-05 seconds \n", + " Time to transform decomposed _PauliX circuit to Clifford+T: 1.291598891839385e-05 seconds\n", + " Time to decompose high level PhaseOffset circuit: 8.141604484990239e-05 seconds \n", + " Time to transform decomposed PhaseOffset circuit to Clifford+T: 7.954100146889687e-05 seconds\n", + " Time to decompose high level Trotter_Unitary circuit: 30.226473957998678 seconds \n", + " Time to transform decomposed Trotter_Unitary circuit to Clifford+T: 196.32578545901924 seconds\n", + " Time to decompose high level MeasurementGate circuit: 0.10464495798805729 seconds \n", + " Time to transform decomposed MeasurementGate circuit to Clifford+T: 9.004096500575542e-05 seconds\n", + "Time to estimate Co2O9H12_step(1): 385.4174027919653\n", + "Time to generate circuit for GSEE: 4.458398325368762e-05 seconds\n", + " Time to decompose high level HPowGate circuit: 8.320901542901993e-05 seconds \n", + " Time to transform decomposed HPowGate circuit to Clifford+T: 0.00022504100343212485 seconds\n", + " Time to decompose high level IdentityGate circuit: 1.6792037058621645e-05 seconds \n", + " Time to transform decomposed IdentityGate circuit to Clifford+T: 3.5410048440098763e-06 seconds\n", + " Time to decompose high level _PauliX circuit: 3.7165998946875334e-05 seconds \n", + " Time to transform decomposed _PauliX circuit to Clifford+T: 2.0875013433396816e-05 seconds\n", + " Time to decompose high level PhaseOffset circuit: 6.483402103185654e-05 seconds \n", + " Time to transform decomposed PhaseOffset circuit to Clifford+T: 8.516700472682714e-05 seconds\n", + " Time to decompose high level Trotter_Unitary circuit: 30.743693416996393 seconds \n", + " Time to transform decomposed Trotter_Unitary circuit to Clifford+T: 206.59496729198145 seconds\n", + " Time to decompose high level MeasurementGate circuit: 0.12303324998356402 seconds \n", + " Time to transform decomposed MeasurementGate circuit to Clifford+T: 0.00011495896615087986 seconds\n", + "Time to estimate Co2O9H12_step(2): 397.87495870899875\n", + "Time to generate circuit for GSEE: 5.266699008643627e-05 seconds\n", + " Time to decompose high level HPowGate circuit: 9.712501196190715e-05 seconds \n", + " Time to transform decomposed HPowGate circuit to Clifford+T: 0.0002949159825220704 seconds\n", + " Time to decompose high level IdentityGate circuit: 1.1041993275284767e-05 seconds \n", + " Time to transform decomposed IdentityGate circuit to Clifford+T: 3.0840164981782436e-06 seconds\n", + " Time to decompose high level _PauliX circuit: 3.3374992199242115e-05 seconds \n", + " Time to transform decomposed _PauliX circuit to Clifford+T: 1.7040991224348545e-05 seconds\n", + " Time to decompose high level PhaseOffset circuit: 7.379200542345643e-05 seconds \n", + " Time to transform decomposed PhaseOffset circuit to Clifford+T: 8.50000069476664e-05 seconds\n", + " Time to decompose high level Trotter_Unitary circuit: 30.895769333001226 seconds \n", + " Time to transform decomposed Trotter_Unitary circuit to Clifford+T: 200.4840085420292 seconds\n", + " Time to decompose high level MeasurementGate circuit: 0.12802375003229827 seconds \n", + " Time to transform decomposed MeasurementGate circuit to Clifford+T: 0.00011108297621831298 seconds\n", + "Time to estimate Co2O9H12_step(3): 382.8127836250351\n", + "Time to generate circuit for GSEE: 4.51250234618783e-05 seconds\n", + " Time to decompose high level HPowGate circuit: 0.00011333299335092306 seconds \n", + " Time to transform decomposed HPowGate circuit to Clifford+T: 0.00029216601978987455 seconds\n", + " Time to decompose high level IdentityGate circuit: 1.266703475266695e-05 seconds \n", + " Time to transform decomposed IdentityGate circuit to Clifford+T: 3.4159747883677483e-06 seconds\n", + " Time to decompose high level _PauliX circuit: 2.354203024879098e-05 seconds \n", + " Time to transform decomposed _PauliX circuit to Clifford+T: 1.3583980035036802e-05 seconds\n", + " Time to decompose high level PhaseOffset circuit: 7.599999662488699e-05 seconds \n", + " Time to transform decomposed PhaseOffset circuit to Clifford+T: 9.037501877173781e-05 seconds\n", + " Time to decompose high level Trotter_Unitary circuit: 35.75693075003801 seconds \n", + " Time to transform decomposed Trotter_Unitary circuit to Clifford+T: 177.5295288329944 seconds\n", + " Time to decompose high level MeasurementGate circuit: 0.1389064170070924 seconds \n", + " Time to transform decomposed MeasurementGate circuit to Clifford+T: 0.00010887498501688242 seconds\n", + "Time to estimate Co2O9H12_step(4): 360.92024995799875\n", + "Time to generate circuit for GSEE: 5.2292016334831715e-05 seconds\n", + " Time to decompose high level HPowGate circuit: 9.529199451208115e-05 seconds \n", + " Time to transform decomposed HPowGate circuit to Clifford+T: 0.0003993749851360917 seconds\n", + " Time to decompose high level IdentityGate circuit: 1.133297337219119e-05 seconds \n", + " Time to transform decomposed IdentityGate circuit to Clifford+T: 3.208988346159458e-06 seconds\n", + " Time to decompose high level _PauliX circuit: 2.3374974261969328e-05 seconds \n", + " Time to transform decomposed _PauliX circuit to Clifford+T: 1.4041957911103964e-05 seconds\n", + " Time to decompose high level PhaseOffset circuit: 6.620795466005802e-05 seconds \n", + " Time to transform decomposed PhaseOffset circuit to Clifford+T: 8.650001836940646e-05 seconds\n", + " Time to decompose high level Trotter_Unitary circuit: 31.192532832967117 seconds \n", + " Time to transform decomposed Trotter_Unitary circuit to Clifford+T: 215.71297658298863 seconds\n", + " Time to decompose high level MeasurementGate circuit: 0.21764633303973824 seconds \n", + " Time to transform decomposed MeasurementGate circuit to Clifford+T: 0.0001324170152656734 seconds\n", + "Time to estimate Co2O9H12_step(5): 415.6341856250074\n", + "Time to generate circuit for GSEE: 7.00420350767672e-05 seconds\n", + " Time to decompose high level HPowGate circuit: 9.320798562839627e-05 seconds \n", + " Time to transform decomposed HPowGate circuit to Clifford+T: 0.0005000000237487257 seconds\n", + " Time to decompose high level IdentityGate circuit: 1.4541961718350649e-05 seconds \n", + " Time to transform decomposed IdentityGate circuit to Clifford+T: 4.084024112671614e-06 seconds\n", + " Time to decompose high level _PauliX circuit: 3.137503517791629e-05 seconds \n", + " Time to transform decomposed _PauliX circuit to Clifford+T: 1.429201802238822e-05 seconds\n", + " Time to decompose high level PhaseOffset circuit: 8.366699330508709e-05 seconds \n", + " Time to transform decomposed PhaseOffset circuit to Clifford+T: 9.070796659216285e-05 seconds\n", + " Time to decompose high level Trotter_Unitary circuit: 32.02644895896083 seconds \n", + " Time to transform decomposed Trotter_Unitary circuit to Clifford+T: 196.10679354099557 seconds\n", + " Time to decompose high level MeasurementGate circuit: 0.12948616698849946 seconds \n", + " Time to transform decomposed MeasurementGate circuit to Clifford+T: 0.00010850001126527786 seconds\n", + "Time to estimate Co2O9H12_step(6): 379.2326729579945\n", + "Time to generate circuit for GSEE: 4.7707988414913416e-05 seconds\n", + " Time to decompose high level HPowGate circuit: 9.26250359043479e-05 seconds \n", + " Time to transform decomposed HPowGate circuit to Clifford+T: 0.0003013330278918147 seconds\n", + " Time to decompose high level IdentityGate circuit: 1.3499986380338669e-05 seconds \n", + " Time to transform decomposed IdentityGate circuit to Clifford+T: 3.2919924706220627e-06 seconds\n", + " Time to decompose high level _PauliX circuit: 2.8499984182417393e-05 seconds \n", + " Time to transform decomposed _PauliX circuit to Clifford+T: 1.550000160932541e-05 seconds\n", + " Time to decompose high level PhaseOffset circuit: 6.787502206861973e-05 seconds \n", + " Time to transform decomposed PhaseOffset circuit to Clifford+T: 0.00010554096661508083 seconds\n", + " Time to decompose high level Trotter_Unitary circuit: 18.41857916698791 seconds \n", + " Time to transform decomposed Trotter_Unitary circuit to Clifford+T: 135.1588185839937 seconds\n", + " Time to decompose high level MeasurementGate circuit: 0.07777683297172189 seconds \n", + " Time to transform decomposed MeasurementGate circuit to Clifford+T: 0.00011062499834224582 seconds\n", + "Time to estimate Co2O9H12_step(7): 256.2739529579994\n", + "Time to generate circuit for GSEE: 6.0375023167580366e-05 seconds\n", + " Time to decompose high level HPowGate circuit: 9.545800276100636e-05 seconds \n", + " Time to transform decomposed HPowGate circuit to Clifford+T: 0.0003053330001421273 seconds\n", + " Time to decompose high level IdentityGate circuit: 1.695897663012147e-05 seconds \n", + " Time to transform decomposed IdentityGate circuit to Clifford+T: 7.916998583823442e-06 seconds\n", + " Time to decompose high level _PauliX circuit: 4.012504359707236e-05 seconds \n", + " Time to transform decomposed _PauliX circuit to Clifford+T: 2.1459010895341635e-05 seconds\n", + " Time to decompose high level PhaseOffset circuit: 7.766700582578778e-05 seconds \n", + " Time to transform decomposed PhaseOffset circuit to Clifford+T: 0.00010412500705569983 seconds\n", + " Time to decompose high level Trotter_Unitary circuit: 40.498850084026344 seconds \n", + " Time to transform decomposed Trotter_Unitary circuit to Clifford+T: 200.93332266696962 seconds\n", + " Time to decompose high level MeasurementGate circuit: 0.15808679099427536 seconds \n", + " Time to transform decomposed MeasurementGate circuit to Clifford+T: 0.00011716695735231042 seconds\n", + "Time to estimate Co2O9H12_step(8): 395.24409108399414\n" ] } ], @@ -682,10 +682,12 @@ "trotter_order = 2\n", "trotter_steps = 1\n", "bits_precision = 10\n", + "ev_time =1 \n", "\n", + "extrapolate=True\n", "gse_args = {\n", " 'trotterize' : True,\n", - " 'ev_time' : 1,\n", + " 'ev_time' : ev_time,\n", " 'trot_ord' : trotter_order,\n", " 'trot_num' : trotter_steps\n", "}\n", @@ -700,19 +702,26 @@ " phase_offset = grab_molecular_phase_offset(molecular_hf_energy)\n", " init_state = molecular_hamiltonian_info.initial_state\n", "\n", - " molecular_metadata = EstimateMetaData(\n", + "\n", + " #TODO: Figure out Phase offset in metadata\n", + " molecular_metadata = GSEEMetaData(\n", " id = time.time_ns(),\n", " name=f'Co2O9H12_{idx}',\n", " category='scientific',\n", " size=f'{n_qubits} qubits',\n", " task='Ground State Energy Estimation',\n", - " implementations=f'GSEE, trotter_subprocess, bits_precision={bits_precision}, phase_offset={phase_offset}',\n", + " implementation='GSEE',\n", + " bits_precision=bits_precision,\n", + " evolution_time=ev_time,\n", + " is_extrapolated=extrapolate,\n", + " nsteps=trotter_steps,\n", + " trotter_order=trotter_order,\n", " )\n", "\n", " t0 = time.perf_counter()\n", " molecular_gse = gsee_resource_estimation(\n", " outdir='GSE/Quantum_Chemistry/',\n", - " numsteps=trotter_steps,\n", + " nsteps=trotter_steps,\n", " gsee_args=gse_args,\n", " init_state=init_state,\n", " precision_order=1,\n", @@ -720,6 +729,7 @@ " phase_offset=phase_offset,\n", " circuit_name=f'Co2O9H12_{idx}',\n", " metadata=molecular_metadata,\n", + " is_extrapolated=extrapolate,\n", " write_circuits=True\n", " )\n", " t1 = time.perf_counter()\n", @@ -768,7 +778,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3 (ipykernel)", + "display_name": "qc-apps", "language": "python", "name": "python3" }, @@ -782,7 +792,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.12.0" + "version": "3.11.10" } }, "nbformat": 4, diff --git a/notebooks/RuClExample.ipynb b/notebooks/RuClExample.ipynb index 9d80713..a9663e2 100644 --- a/notebooks/RuClExample.ipynb +++ b/notebooks/RuClExample.ipynb @@ -50,7 +50,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "/Users/jonhas/anaconda3/envs/other/lib/python3.12/site-packages/cotengra/hyperoptimizers/hyper.py:33: UserWarning: Couldn't import `kahypar` - skipping from default hyper optimizer and using basic `labels` method instead.\n", + "/Users/gsgrattan/.conda/envs/qc-apps/lib/python3.11/site-packages/cotengra/hyperoptimizers/hyper.py:33: UserWarning: Couldn't import `kahypar` - skipping from default hyper optimizer and using basic `labels` method instead.\n", " warnings.warn(\n" ] } @@ -72,7 +72,7 @@ "from qca.utils.algo_utils import estimate_qsp, estimate_trotter\n", "from pyLIQTR.gate_decomp.cirq_transforms import clifford_plus_t_direct_transform\n", "\n", - "from qca.utils.utils import plot_histogram, gen_resource_estimate, re_as_json, EstimateMetaData\n", + "from qca.utils.utils import plot_histogram, gen_resource_estimate, re_as_json, EstimateMetaData, QSPMetaData, TrotterizationMetaData\n", "from qca.utils.hamiltonian_utils import flatten_nx_graph, assign_hexagon_labels, pyliqtr_hamiltonian_to_openfermion_qubit_operator" ] }, @@ -240,7 +240,7 @@ "outputs": [ { "data": { - "image/png": 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", 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", 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", + "image/png": 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", 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" ] @@ -974,17 +974,17 @@ "output_type": "stream", "text": [ "Estimating RuCl row 13 using Trotterization\n", - "Time to estimate number of trotter steps required (215647636): 61.44379833400126 seconds\n", - "Time to find term ordering: 0.09191362499950628 seconds\n", - "Time to generate trotter circuit from openfermion: 1.0667001333786175e-05 seconds\n", - "Time to generate a clifford + T circuit from trotter circuit: 291.2586447499998 seconds\n", - "Total time to estimate RuCl row 13: 467.4064990000006 seconds\n", + "Time to estimate number of trotter steps required (215647636): 38.72402595798485 seconds\n", + "Time to find term ordering: 0.025059750012587756 seconds\n", + "Time to generate trotter circuit from openfermion: 1.0840012691915035e-06 seconds\n", + "Time to generate a clifford + T circuit from trotter circuit: 176.23969008401036 seconds\n", + "Total time to estimate RuCl row 13: 285.9646506670397 seconds\n", "\n" ] }, { "data": { - "image/png": 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kZGjDhg0KCQnRqVOncg07Bw8elKRsz5WXl5fTF6O8uPXWW7Ndw6hcuXLaunVrvpZztZCQEOvw4/33369XXnlFd911l/bu3Wsdrnr66afVqlUr9e7dO1/LXrx4sTw9PdWnT58bqhG5I+ygUBT2mT5Xy8zM1F133aXRo0fnOP+2225zup3f+ipUqGB9EEdHR6tu3brq0aOH3nzzTWvw7tVvslmuvl5OrVq1VKpUKWtAbFG4ke3h5eWliIgIrV27Vvv27VNiYqLatm2rkJAQXbx4UfHx8Vq3bp3q1q2br71l19OqVStVrlxZixcvzjXstGjRwvrAlKQJEyZc9wKMnp6e+WrP2guQNdj9tddeu+apz/7+/kpPT8/18a/nlVde0bhx4/S3v/1NL730koKDg+Xh4aERI0Y4DbjPa92FpU2bNnr55ZetwPvCCy8oKChIDRs21Lp166yAcCN7/PKjqJ6H+++/Xy+88II+//xzDR06VKtWrdKKFSv03//+12lA+6VLl3T+/HkdOHBAwcHB1hedLOfPn9eyZcsUFRWVp7FcKDjCDgrkWh/s11KxYkWVLl1au3fvzjbv119/lYeHh/WtOrdlX2tezZo19eeff1qBpLB1795d7du31yuvvKKhQ4eqTJky1rfpq8/QuPKDWJJKly6tTp06adWqVTp8+HC2vQlFpXr16tfcHlnzs7Rt21bTpk3Td999pwoVKqhu3bpyOBxq0KCB1q1bp3Xr1uUaSAoqLS1NKSkpufZZvHixzp8/b93O796A/KhZs6aky3vncnutVaxYUX5+ftaeoCvl9Jxf7dNPP1XHjh313nvvObUnJydbJwS4g7Zt2+rChQv68MMPdeTIESvUtGvXzgo7t912W64f5Fmvs71796pTp05W+8WLF5WQkKDGjRtbbfl93yksWa+3rNfmoUOHJF0+eeNqR44cUXh4uN544w2NGDHCad7y5ct15swZDmEVAcbsoECyLvKW19OCPT091aVLF33++edO33ySkpK0ZMkStWnTxvrWk9uyy5Qpk2P7gw8+qLi4OH377bfZ5iUnJ+vSpUt5qjM/nn/+eZ08eVLvvPOOpMtv2p6entnGB82dOzfbfSdMmCBjjB555JEcx6Vs2rRJixYtcnnNV7r77rv1448/Ol3s7+zZs3r77bcVFhbmNOaqbdu2Sk9P18yZM9WmTRvrQ6dt27b64IMPdPTo0QJ/ez979qzOnTuXrf0///mPTp8+rebNm+d6/9atWysqKsqaCjPsNGvWTDVr1tTrr7+e43bLuuKzp6enoqOj9dlnn1kfhJK0a9euHF+jV/P09My2N2Lp0qU6cuTIDa6Ba0VERMjLy0vTpk1TcHCwdRi6bdu22rBhg9asWXPd10Xz5s1VsWJFzZs3TxcuXLDaFy5cmO1/Pb/vO9eS11PP//jjjxz3Cr377ruSZL02O3XqpGXLlmWbKlasqObNm2vZsmW65557si1nyZIlKl26tP7yl7/c0Prg+tizgwJp1qyZJOmFF15Q37595eXlpXvuuSfXK91OmTJFK1euVJs2bfTEE0+oVKlSmj9/vtLT052uhdGkSRN5enpq2rRpSklJkY+Pjzp16qRKlSqpWbNmeuuttzRlyhTVqlVLlSpVUqdOnfTcc89p+fLl6tGjhwYMGKBmzZrp7Nmz2rZtmz799FMdOHDA5d+Iu3XrpoYNG2rGjBkaNmyYAgMD9cADD2j27NlyOByqWbOmvvzyy2zjhaTLh2jmzJmjJ554QnXr1nW6gnJsbKyWL1+uKVOm5Pr4DodD7du3L/Dl/MeMGaMPP/xQ3bp101NPPaXg4GAtWrRICQkJ+s9//uN0Rd/IyEiVKlVKu3fv1pAhQ6z2du3a6a233pKU86GKrHXYsWOHpMvXIPn+++8lSS+++KKky9/oo6Ki1KdPH9WtW1ceHh7auHGj/v3vfyssLExPP/10gdavMHh4eOjdd99Vt27d1KBBAw0cOFC33HKLjhw5otWrVysgIEBffPGFpMvXUlqxYoXatm2rJ554QpcuXdLs2bPVoEGD644h6dGjhyZPnqyBAweqVatW2rZtmxYvXlyoQa4gSpcurWbNmmnDhg3WNXaky6+Ls2fP6uzZs9cNO15eXpoyZYqGDh2qTp06qU+fPkpISNCCBQuyrW/NmjUVFBSkefPmqWzZsipTpowiIiLyPQYvr6ee//vf/9a8efOsEyvOnDmjb7/9VitXrtQ999xj7YmqVq1ajpeRGDFihEJCQtSzZ89s806dOqVvvvlGvXv3LvDlGpAPxXYeGEq8l156ydxyyy3Gw8PD6fRcXXVK9pU2b95soqOjjb+/vyldurTp2LGjWb9+fbZ+77zzjqlRo4Z1mm7WaaqJiYmme/fupmzZstlOSz1z5owZO3asqVWrlvH29jYVKlQwrVq1Mq+//rq5cOGCMeb/nwb+2muv5Xk9czt9dOHChU6nwp44ccL07t3blC5d2pQrV84MHTrUbN++/Zqny27atMn89a9/NVWqVDFeXl6mXLlypnPnzmbRokVOpx7rqlPPz5w5YySZvn373lD9v/32m7n//vtNUFCQ8fX1NS1btjRffvlljn1btGhhJJn4+Hir7ffffzeSTNWqVXO8j644XffqKcuJEyfMkCFDTN26dU2ZMmWMt7e3qV27thkxYoQ5ceLEddcvv3J6fV7rdZF1mvTSpUud2n/++WfTq1cvU758eePj42OqV69uHnzwQRMTE+PUb82aNaZZs2bG29vb1KhRw8ybN89MmDAhT6eeP/vss6Zy5crGz8/PtG7d2sTFxZn27ds7veavVd/VlzvIi/yeep7lueeeM5LMtGnTnNpr1aplJDldauLKmq++DMHcuXNNeHi48fHxMc2bNzdr167Ntr7GGPP555+b+vXrm1KlSjmtY/v27U2DBg2y1de/f39TvXp1p7a8nnr+008/mQceeMBUq1bN+Pj4mDJlypimTZuaGTNmmIsXL173/rn9782bN89IMsuXL7/ucnDjHMYU8gg2AC739ddfq0ePHvrll1/UqFGj4i4HANwaY3aAEmj16tXq27cvQQcA8oA9OwAAwNbYswMAAGyNsAMAAGyNsAMAAGyNsAMAAGyNiwrq8u/dHD16VGXLlnWby5EDAIDcGWN05swZValSxelCqFcj7Eg6evRosf0+EQAAuDGHDx/Wrbfees35hB1JZcuWlXT5ybr6V2kBAIB7Sk1NVdWqVa3P8Wsh7Oj//5JuQEAAYQcAgBLmekNQGKAMAABsjbADAABsjbADAABsrVjDztq1a3XPPfeoSpUqcjgc+uyzz5zmG2M0fvx4Va5cWX5+foqKitLevXud+pw6dUr9+vVTQECAgoKCNGjQIP35559FuBYAAMCdFWvYOXv2rBo3bqw5c+bkOH/69OmaNWuW5s2bp/j4eJUpU0bR0dFKS0uz+vTr1087duzQypUr9eWXX2rt2rUaMmRIUa0CAABwc27zq+cOh0PLli1Tz549JV3eq1OlShU9++yzGjVqlCQpJSVFISEhWrhwofr27atdu3apfv36+umnn9S8eXNJ0ooVK3T33Xfr999/V5UqVfL02KmpqQoMDFRKSgpnYwEAUELk9fPbbcfsJCQkKDExUVFRUVZbYGCgIiIiFBcXJ0mKi4tTUFCQFXQkKSoqSh4eHoqPjy/ymgEAgPtx2+vsJCYmSpJCQkKc2kNCQqx5iYmJqlSpktP8UqVKKTg42OqTk/T0dKWnp1u3U1NTXVU2AABwM267Z6cwTZ06VYGBgdbET0UAAGBfbht2QkNDJUlJSUlO7UlJSda80NBQHT9+3Gn+pUuXdOrUKatPTsaOHauUlBRrOnz4sIurBwAA7sJtw054eLhCQ0MVExNjtaWmpio+Pl6RkZGSpMjISCUnJ2vTpk1Wn1WrVikzM1MRERHXXLaPj4/10xD8RAQAAPZWrGN2/vzzT+3bt8+6nZCQoC1btig4OFjVqlXTiBEjNGXKFNWuXVvh4eEaN26cqlSpYp2xVa9ePXXt2lWDBw/WvHnzdPHiRQ0fPlx9+/bN85lYAADA3oo17GzcuFEdO3a0bo8cOVKS1L9/fy1cuFCjR4/W2bNnNWTIECUnJ6tNmzZasWKFfH19rfssXrxYw4cPV+fOneXh4aHevXtr1qxZRb4uAADAPbnNdXaKE9fZAQCg5Cnx19kBAABwBcJOEQsb81VxlwAAwE2FsAMAAGyNsAMAAGyNsAMAAGyNsAMAAGyNsAMAAGyNsAMAAGyNsAMAAGyNsAMAAGyNsAMAAGyNsAMAAGyNsAMAAGyNsAMAAGyNsAMAAGyNsAMAAGyNsAMAAGyNsAMAAGyNsAMAAGyNsAMAAGyNsAMAAGyNsAMAAGyNsAMAAGyNsAMAAGyNsAMAAGyNsAMAAGyNsAMAAGyNsAMAAGyNsAMAAGyNsAMAAGyNsAMAAGyNsAMAAGyNsAMAAGyNsAMAAGyNsAMAAGyNsAMAAGyNsAMAAGyNsAMAAGyNsAMAAGyNsAMAAGyNsAMAAGyNsAMAAGyNsAMAAGyNsAMAAGyNsAMAAGyNsAMAAGyNsAMAAGyNsAMAAGyNsAMAAGyNsAMAAGyNsAMAAGyNsAMAAGyNsAMAAGyNsAMAAGyNsAMAAGyNsAMAAGyNsAMAAGyNsAMAAGyNsAMAAGyNsAMAAGyNsAMAAGzNrcNORkaGxo0bp/DwcPn5+almzZp66aWXZIyx+hhjNH78eFWuXFl+fn6KiorS3r17i7FqAADgTtw67EybNk1vvfWW/vnPf2rXrl2aNm2apk+frtmzZ1t9pk+frlmzZmnevHmKj49XmTJlFB0drbS0tGKsHAAAuItSxV1AbtavX6/77rtP3bt3lySFhYXpww8/1I8//ijp8l6dmTNn6sUXX9R9990nSXr//fcVEhKizz77TH379i222gEAgHtw6z07rVq1UkxMjPbs2SNJ+uWXX/T999+rW7dukqSEhAQlJiYqKirKuk9gYKAiIiIUFxd3zeWmp6crNTXVaQIAAPbk1nt2xowZo9TUVNWtW1eenp7KyMjQyy+/rH79+kmSEhMTJUkhISFO9wsJCbHm5WTq1KmaNGlS4RUOAADchlvv2fnkk0+0ePFiLVmyRJs3b9aiRYv0+uuva9GiRTe03LFjxyolJcWaDh8+7KKKAQCAu3HrPTvPPfecxowZY429adSokQ4ePKipU6eqf//+Cg0NlSQlJSWpcuXK1v2SkpLUpEmTay7Xx8dHPj4+hVo7AABwD269Z+fcuXPy8HAu0dPTU5mZmZKk8PBwhYaGKiYmxpqfmpqq+Ph4RUZGFmmtAADAPbn1np177rlHL7/8sqpVq6YGDRro559/1owZM/S3v/1NkuRwODRixAhNmTJFtWvXVnh4uMaNG6cqVaqoZ8+exVs8AABwC24ddmbPnq1x48bpiSee0PHjx1WlShUNHTpU48ePt/qMHj1aZ8+e1ZAhQ5ScnKw2bdpoxYoV8vX1LcbKAQCAu3CYKy9HfJNKTU1VYGCgUlJSFBAQUKiPFTbmKx14tXuhPgYAADeDvH5+u/WYHQAAgBtF2AEAALZG2AEAALZG2AEAALZG2AEAALZG2AEAALZG2AEAALZG2AEAALZG2AEAALZG2AEAALZG2AEAALZG2AEAALZG2AEAALZG2AEAALZG2AEAALZG2AEAALZG2AEAALZG2AEAALZG2AEAALZG2AEAALZG2AEAALZG2AEAALZG2AEAALZG2AEAALZG2AEAALZG2AEAALZG2AEAALZG2AEAALZG2AEAALZG2AEAALZG2AEAALZG2AEAALZG2AEAALZG2AEAALZG2AEAALZG2AEAALZG2AEAALZG2AEAALZG2AEAALZG2AEAALZG2AEAALZG2AEAALZG2AEAALZG2AEAALZG2IHbCBvzVXGXAACwIcIOAACwNcIOAACwNcIOAACwNcIOAACwNcIOAACwNcIOAACwNcIOAACwNcIOAACwNcIOAACwNcIOAACwNcIOAACwNcIOAACwNcIOAACwNcIOAACwNcIOAACwNcIOAACwNbcPO0eOHNHDDz+s8uXLy8/PT40aNdLGjRut+cYYjR8/XpUrV5afn5+ioqK0d+/eYqwYAAC4E7cOO6dPn1br1q3l5eWlb775Rjt37tQ//vEPlStXzuozffp0zZo1S/PmzVN8fLzKlCmj6OhopaWlFWPlAADAXZQq7gJyM23aNFWtWlULFiyw2sLDw62/jTGaOXOmXnzxRd13332SpPfff18hISH67LPP1Ldv3yKvGQAAuBe33rOzfPlyNW/eXA888IAqVaqkO+64Q++88441PyEhQYmJiYqKirLaAgMDFRERobi4uGsuNz09XampqU4TAACwJ7cOO/v379dbb72l2rVr69tvv9Xjjz+up556SosWLZIkJSYmSpJCQkKc7hcSEmLNy8nUqVMVGBhoTVWrVi28lUCehI35qrhLAADYlFuHnczMTDVt2lSvvPKK7rjjDg0ZMkSDBw/WvHnzbmi5Y8eOVUpKijUdPnzYRRUDAAB349Zhp3Llyqpfv75TW7169XTo0CFJUmhoqCQpKSnJqU9SUpI1Lyc+Pj4KCAhwmgAAgD25ddhp3bq1du/e7dS2Z88eVa9eXdLlwcqhoaGKiYmx5qempio+Pl6RkZFFWisAAHBPbh12nnnmGW3YsEGvvPKK9u3bpyVLlujtt9/WsGHDJEkOh0MjRozQlClTtHz5cm3btk2PPvqoqlSpop49exZv8cgTxuoAAAqbW5963qJFCy1btkxjx47V5MmTFR4erpkzZ6pfv35Wn9GjR+vs2bMaMmSIkpOT1aZNG61YsUK+vr7FWDkAAHAXbh12JKlHjx7q0aPHNec7HA5NnjxZkydPLsKqAABASeHWh7EAAABuFGEHAADYGmEHAADYGmEHAADYGmEHAADYGmEHAADYWoHCTo0aNXTy5Mls7cnJyapRo8YNFwUAAOAqBQo7Bw4cUEZGRrb29PR0HTly5IaLAgAAcJV8XVRw+fLl1t/ffvutAgMDrdsZGRmKiYlRWFiYy4rDzSdszFc68Gr34i4DAGAj+Qo7Wb835XA41L9/f6d5Xl5eCgsL0z/+8Q+XFQcAAHCj8hV2MjMzJV3+tfGffvpJFSpUKJSiAAAAXKVAv42VkJDg6joAAAAKRYF/CDQmJkYxMTE6fvy4tccny7/+9a8bLgwAAMAVChR2Jk2apMmTJ6t58+aqXLmyHA6Hq+sCAABwiQKFnXnz5mnhwoV65JFHXF0PAACASxXoOjsXLlxQq1atXF0LAACAyxUo7Pzf//2flixZ4upaAAAAXK5Ah7HS0tL09ttv67vvvtPtt98uLy8vp/kzZsxwSXEAAAA3qkBhZ+vWrWrSpIkkafv27U7zGKyMvAob81VxlwAAuAkUKOysXr3a1XUAAAAUigKN2QEAACgpCrRnp2PHjrkerlq1alWBCwIAAHClAoWdrPE6WS5evKgtW7Zo+/bt2X4gFLgexu4AAApTgcLOG2+8kWP7xIkT9eeff95QQQAAAK7k0jE7Dz/8ML+LBQAA3IpLw05cXJx8fX1duUgAAIAbUqDDWL169XK6bYzRsWPHtHHjRo0bN84lhQEAALhCgcJOYGCg020PDw/VqVNHkydPVpcuXVxSGAAAgCsUKOwsWLDA1XUAAAAUigKFnSybNm3Srl27JEkNGjTQHXfc4ZKiAAAAXKVAYef48ePq27evYmNjFRQUJElKTk5Wx44d9dFHH6lixYqurBEAAKDACnQ21pNPPqkzZ85ox44dOnXqlE6dOqXt27crNTVVTz31lKtrBAAAKLAC7dlZsWKFvvvuO9WrV89qq1+/vubMmcMAZQAA4FYKtGcnMzNTXl5e2dq9vLyUmZl5w0XdDPiJBAAAikaBwk6nTp309NNP6+jRo1bbkSNH9Mwzz6hz584uKw4AAOBGFSjs/POf/1RqaqrCwsJUs2ZN1axZU+Hh4UpNTdXs2bNdXSMAAECBFWjMTtWqVbV582Z99913+vXXXyVJ9erVU1RUlEuLw80pbMxXOvBq9+IuAwBgE/nas7Nq1SrVr19fqampcjgcuuuuu/Tkk0/qySefVIsWLdSgQQOtW7eusGoFAADIt3yFnZkzZ2rw4MEKCAjINi8wMFBDhw7VjBkzXFYcAADAjcpX2Pnll1/UtWvXa87v0qWLNm3adMNFAQAAuEq+wk5SUlKOp5xnKVWqlE6cOHHDRQEAALhKvsLOLbfcou3bt19z/tatW1W5cuUbLgoAAMBV8hV27r77bo0bN05paWnZ5p0/f14TJkxQjx49XFYcAADAjcrXqecvvvii/vvf/+q2227T8OHDVadOHUnSr7/+qjlz5igjI0MvvPBCoRQKAABQEPkKOyEhIVq/fr0ef/xxjR07VsYYSZLD4VB0dLTmzJmjkJCQQikUAACgIPJ9UcHq1avr66+/1unTp7Vv3z4ZY1S7dm2VK1euMOoDAAC4IQW6grIklStXTi1atHBlLQAAAC5XoN/GAm4Uv/oOACgqhB0AAGBrhB0AAGBrhB0AAGBrhJ1ixLgVAAAKH2EHAADYGmEHAADYGmGnGHD4CgCAokPYAQAAtkbYAQAAtkbYAQAAtkbYAQAAtkbYAQAAtkbYAQAAtlaiws6rr74qh8OhESNGWG1paWkaNmyYypcvL39/f/Xu3VtJSUnFVyQAAHArJSbs/PTTT5o/f75uv/12p/ZnnnlGX3zxhZYuXao1a9bo6NGj6tWrVzFVCQAA3E2JCDt//vmn+vXrp3feeUflypWz2lNSUvTee+9pxowZ6tSpk5o1a6YFCxZo/fr12rBhQzFWDAAA3EWJCDvDhg1T9+7dFRUV5dS+adMmXbx40am9bt26qlatmuLi4q65vPT0dKWmpjpNAADAntw+7Hz00UfavHmzpk6dmm1eYmKivL29FRQU5NQeEhKixMTEay5z6tSpCgwMtKaqVau6umzcIH5SAwDgKm4ddg4fPqynn35aixcvlq+vr8uWO3bsWKWkpFjT4cOHXbZsAADgXtw67GzatEnHjx9X06ZNVapUKZUqVUpr1qzRrFmzVKpUKYWEhOjChQtKTk52ul9SUpJCQ0OvuVwfHx8FBAQ4TQAAwJ5KFXcBuencubO2bdvm1DZw4EDVrVtXzz//vKpWrSovLy/FxMSod+/ekqTdu3fr0KFDioyMLI6SAQCAm3HrsFO2bFk1bNjQqa1MmTIqX7681T5o0CCNHDlSwcHBCggI0JNPPqnIyEjdeeedxVEyriNszFc68Gr34i4DAHATceuwkxdvvPGGPDw81Lt3b6Wnpys6Olpz584t7rIAAICbKHFhJzY21um2r6+v5syZozlz5hRPQQAAwK259QBlAACAG0XYAQAAtkbYAQAAtkbYAQAAtkbYQYHxkw4AgJKAsAMAAGyNsAMAAGyNsAO3VZiHyTgEBwA3D8IOAACwNcIOAACwNcIOAACwNcIOAACwNcIOAACwNcIOAACwNcIOAACwNcIOAACwNcIOAACwNcIOAACwNcIOAACwNcIOAACwNcIOAACwNcIOAACwNcJOEQob81Vxl+AydloXAIC9EXYAAICtEXYAAICtEXaQL2FjvrrmISwObQEA3BFhBwAA2BphBwAA2BphBwAA2BphBwAA2BphBwAA2BphBwAA2BphBwAA2BphBzctrgsEADcHwg4AALA1wg4AALA1wg4AALA1wg4AALA1wg4AALA1wg4AALA1wg4AALA1wg4AALA1wg4AALA1wg5uSNZViPNzNeLC6pvX5XHlZAC4uRB2AACArRF2AACArRF2AACArRF2AACArRF2AACArRF2AACArRF2AACArRF2kGd2vT7Nletl13UEgJsZYQcAANgaYQcAANgaYQc3LK+HfjhEBAAoDoQdAABga4QdAABga4QdAABga4QdFIqSMj6npNQJACg4wg4AALA1wg4AALA1tw47U6dOVYsWLVS2bFlVqlRJPXv21O7du536pKWladiwYSpfvrz8/f3Vu3dvJSUlFVPFAADA3bh12FmzZo2GDRumDRs2aOXKlbp48aK6dOmis2fPWn2eeeYZffHFF1q6dKnWrFmjo0ePqlevXsVYNQAAcCeliruA3KxYscLp9sKFC1WpUiVt2rRJ7dq1U0pKit577z0tWbJEnTp1kiQtWLBA9erV04YNG3TnnXcWR9kAAMCNuPWenaulpKRIkoKDgyVJmzZt0sWLFxUVFWX1qVu3rqpVq6a4uLhrLic9PV2pqalOEwAAsKcSE3YyMzM1YsQItW7dWg0bNpQkJSYmytvbW0FBQU59Q0JClJiYeM1lTZ06VYGBgdZUtWrVwiz9phI25qsSeTp3SawZAJA3JSbsDBs2TNu3b9dHH310w8saO3asUlJSrOnw4cMuqBAAALgjtx6zk2X48OH68ssvtXbtWt16661We2hoqC5cuKDk5GSnvTtJSUkKDQ295vJ8fHzk4+NTmCUDAAA34dZ7dowxGj58uJYtW6ZVq1YpPDzcaX6zZs3k5eWlmJgYq2337t06dOiQIiMji7pc5KAkHR4qSbUCAPLOrffsDBs2TEuWLNHnn3+usmXLWuNwAgMD5efnp8DAQA0aNEgjR45UcHCwAgIC9OSTTyoyMpIzsQAAgCQ3DztvvfWWJKlDhw5O7QsWLNCAAQMkSW+88YY8PDzUu3dvpaenKzo6WnPnzi3iSgEAgLty67BjjLluH19fX82ZM0dz5swpgooAAEBJ49Zjdm4GN8s4kZK2niWtXgDAtRF2AACArRF2AACArRF2AACArRF2YHv5HX/DeB0AsBfCDgAAsDXCDgAAsDXCDgodh4UAAMWJsAMAAGyNsAMAAGyNsAMAAGyNsIM8YdwNAKCkIuwAAABbI+wAAABbI+zA7bnqEBqH4gDg5kTYAQAAtkbYAQAAtkbYAQAAtkbYwXUVdKyLK8fIhI35ijE3AIACIewAAABbI+wAAABbI+wAAABbI+wAAABbI+wAAABbI+wAAABbI+wUMk6XBgCgeBF2AACArRF2AACArRF2AACArRF2cFNg7BQA3LwIOwAAwNYIOwAAwNYIO7AlDlsBALIQdgAAgK0RdgAAgK0RdgAAgK0RdmBrNzJ2h3E/AGAPhB0AAGBrhB0AAGBrhB0AAGBrpYq7gJtBSR374Y51h435Sgde7X7dPgAAZGHPDgAAsDXCDgAAsDXCDpALDokBQMlH2AEAALZG2AEAALZG2AEAALZG2EGJk9dxNMUx3oYxPgDgfgg7AADA1gg7AADA1gg7KJFyOlxUmIeQStLhqZJUKwAUBcIOAACwNcIOAACwNcIOAACwNcIOclSSxn1cWWth1F2SnossJbFmd8TzCNgDYQcAANgaYQcAANgaYQcAANgaYcfmrh5zkJcxCCVlnEJhj9XJ7fFc0c9Vrvc8FPVzU1JePze7krydSnLtKB6EHQAAYGu2CTtz5sxRWFiYfH19FRERoR9//LG4SwIAAG7AFmHn448/1siRIzVhwgRt3rxZjRs3VnR0tI4fP17cpeVJ1i7Za+2avd783O7jynnuqLgOGV3vcXPq5+rDYEW17mFjviq218WVj52fOq53+LYo/weuXof89Hd1HYW5/IK4kf+T4uZOh85ddT87s0XYmTFjhgYPHqyBAweqfv36mjdvnkqXLq1//etfxV0aAAAoZiU+7Fy4cEGbNm1SVFSU1ebh4aGoqCjFxcUVY2UAAMAdlCruAm7UH3/8oYyMDIWEhDi1h4SE6Ndff83xPunp6UpPT7dup6SkSJJSU1NdXl9m+rk89UtNTVVm+rkca8hqv9b8az1uTvfJquday8lrvTez622ra/XL6/bLb7+rH+PKx8/P8nJ7nCuXd72ab/TxrvXYeakjp3rycvta93XFuly9DtdbXn7WM791XPk8FsZj5Ne1XsN5eY7cpXZ3fAx3eH6KStZ6GmNy72hKuCNHjhhJZv369U7tzz33nGnZsmWO95kwYYKRxMTExMTExGSD6fDhw7lmhRK/Z6dChQry9PRUUlKSU3tSUpJCQ0NzvM/YsWM1cuRI63ZmZqZOnTql8uXLy+FwuKy21NRUVa1aVYcPH1ZAQIDLlgvXYPu4N7aP+2LbuLebafsYY3TmzBlVqVIl134lPux4e3urWbNmiomJUc+ePSVdDi8xMTEaPnx4jvfx8fGRj4+PU1tQUFCh1RgQEGD7F1xJxvZxb2wf98W2cW83y/YJDAy8bp8SH3YkaeTIkerfv7+aN2+uli1baubMmTp79qwGDhxY3KUBAIBiZouw06dPH504cULjx49XYmKimjRpohUrVmQbtAwAAG4+tgg7kjR8+PBrHrYqLj4+PpowYUK2Q2ZwD2wf98b2cV9sG/fG9snOYcz1ztcCAAAouUr8RQUBAAByQ9gBAAC2RtgBAAC2RtgBAAC2RtgpRHPmzFFYWJh8fX0VERGhH3/8sbhLsr2JEyfK4XA4TXXr1rXmp6WladiwYSpfvrz8/f3Vu3fvbFffPnTokLp3767SpUurUqVKeu6553Tp0qWiXhVbWLt2re655x5VqVJFDodDn332mdN8Y4zGjx+vypUry8/PT1FRUdq7d69Tn1OnTqlfv34KCAhQUFCQBg0apD///NOpz9atW9W2bVv5+vqqatWqmj59emGvWol3vW0zYMCAbP9LXbt2derDtik8U6dOVYsWLVS2bFlVqlRJPXv21O7du536uOr9LDY2Vk2bNpWPj49q1aqlhQsXFvbqFTnCTiH5+OOPNXLkSE2YMEGbN29W48aNFR0drePHjxd3abbXoEEDHTt2zJq+//57a94zzzyjL774QkuXLtWaNWt09OhR9erVy5qfkZGh7t2768KFC1q/fr0WLVqkhQsXavz48cWxKiXe2bNn1bhxY82ZMyfH+dOnT9esWbM0b948xcfHq0yZMoqOjlZaWprVp1+/ftqxY4dWrlypL7/8UmvXrtWQIUOs+ampqerSpYuqV6+uTZs26bXXXtPEiRP19ttvF/r6lWTX2zaS1LVrV6f/pQ8//NBpPtum8KxZs0bDhg3Thg0btHLlSl28eFFdunTR2bNnrT6ueD9LSEhQ9+7d1bFjR23ZskUjRozQ//3f/+nbb78t0vUtdC75NU5k07JlSzNs2DDrdkZGhqlSpYqZOnVqMVZlfxMmTDCNGzfOcV5ycrLx8vIyS5cutdp27dplJJm4uDhjjDFff/218fDwMImJiVaft956ywQEBJj09PRCrd3uJJlly5ZZtzMzM01oaKh57bXXrLbk5GTj4+NjPvzwQ2OMMTt37jSSzE8//WT1+eabb4zD4TBHjhwxxhgzd+5cU65cOaft8/zzz5s6deoU8hrZx9Xbxhhj+vfvb+67775r3odtU7SOHz9uJJk1a9YYY1z3fjZ69GjToEEDp8fq06ePiY6OLuxVKlLs2SkEFy5c0KZNmxQVFWW1eXh4KCoqSnFxccVY2c1h7969qlKlimrUqKF+/frp0KFDkqRNmzbp4sWLTtulbt26qlatmrVd4uLi1KhRI6erb0dHRys1NVU7duwo2hWxuYSEBCUmJjptj8DAQEVERDhtj6CgIDVv3tzqExUVJQ8PD8XHx1t92rVrJ29vb6tPdHS0du/erdOnTxfR2thTbGysKlWqpDp16ujxxx/XyZMnrXlsm6KVkpIiSQoODpbkuvezuLg4p2Vk9bHbZxVhpxD88ccfysjIyPZzFSEhIUpMTCymqm4OERERWrhwoVasWKG33npLCQkJatu2rc6cOaPExER5e3tn+9HXK7dLYmJijtstax5cJ+v5zO3/JDExUZUqVXKaX6pUKQUHB7PNClnXrl31/vvvKyYmRtOmTdOaNWvUrVs3ZWRkSGLbFKXMzEyNGDFCrVu3VsOGDSXJZe9n1+qTmpqq8+fPF8bqFAvb/FwEIEndunWz/r799tsVERGh6tWr65NPPpGfn18xVgaULH379rX+btSokW6//XbVrFlTsbGx6ty5czFWdvMZNmyYtm/f7jT+EPnDnp1CUKFCBXl6emYbFZ+UlKTQ0NBiqurmFBQUpNtuu0379u1TaGioLly4oOTkZKc+V26X0NDQHLdb1jy4Ttbzmdv/SWhoaLZB/ZcuXdKpU6fYZkWsRo0aqlChgvbt2yeJbVNUhg8fri+//FKrV6/WrbfearW76v3sWn0CAgJs9QWRsFMIvL291axZM8XExFhtmZmZiomJUWRkZDFWdvP5888/9dtvv6ly5cpq1qyZvLy8nLbL7t27dejQIWu7REZGatu2bU5v4itXrlRAQIDq169f5PXbWXh4uEJDQ522R2pqquLj4522R3JysjZt2mT1WbVqlTIzMxUREWH1Wbt2rS5evGj1WblyperUqaNy5coV0drY3++//66TJ0+qcuXKktg2hc0Yo+HDh2vZsmVatWqVwsPDnea76v0sMjLSaRlZfWz3WVXcI6Tt6qOPPjI+Pj5m4cKFZufOnWbIkCEmKCjIaVQ8XO/ZZ581sbGxJiEhwfzwww8mKirKVKhQwRw/ftwYY8xjjz1mqlWrZlatWmU2btxoIiMjTWRkpHX/S5cumYYNG5ouXbqYLVu2mBUrVpiKFSuasWPHFtcqlWhnzpwxP//8s/n555+NJDNjxgzz888/m4MHDxpjjHn11VdNUFCQ+fzzz83WrVvNfffdZ8LDw8358+etZXTt2tXccccdJj4+3nz//femdu3a5qGHHrLmJycnm5CQEPPII4+Y7du3m48++siULl3azJ8/v8jXtyTJbducOXPGjBo1ysTFxZmEhATz3XffmaZNm5ratWubtLQ0axlsm8Lz+OOPm8DAQBMbG2uOHTtmTefOnbP6uOL9bP/+/aZ06dLmueeeM7t27TJz5swxnp6eZsWKFUW6voWNsFOIZs+ebapVq2a8vb1Ny5YtzYYNG4q7JNvr06ePqVy5svH29ja33HKL6dOnj9m3b581//z58+aJJ54w5cqVM6VLlzZ/+ctfzLFjx5yWceDAAdOtWzfj5+dnKlSoYJ599llz8eLFol4VW1i9erWRlG3q37+/Meby6efjxo0zISEhxsfHx3Tu3Nns3r3baRknT540Dz30kPH39zcBAQFm4MCB5syZM059fvnlF9OmTRvj4+NjbrnlFvPqq68W1SqWWLltm3PnzpkuXbqYihUrGi8vL1O9enUzePDgbF/W2DaFJ6dtI8ksWLDA6uOq97PVq1ebJk2aGG9vb1OjRg2nx7ALhzHGFPXeJAAAgKLCmB0AAGBrhB0AAGBrhB0AAGBrhB0AAGBrhB0AAGBrhB0AAGBrhB0AAGBrhB0Atrdw4cJsvw59tYkTJ6pJkya59jlw4IAcDoe2bNnistoAFD7CDoBi4XA4cp0mTpyY7T5jxoxR3bp1ndp+/fVXORwODRgwwKl94cKF8vHx0fnz59WnTx/t2bMnX/UNGDBAPXv2zOdaAXBHpYq7AAA3p2PHjll/f/zxxxo/frx2795ttfn7+2e7T8eOHTVt2jQlJiZav9q8evVqVa1aVbGxsU59V69erTvvvNP65WY7/YIzgPxhzw6AYhEaGmpNgYGBcjgcTm05hZ02bdrIy8vLKdjExsZq2LBhOnXqlA4cOODU3rFjR0k5H8Z69dVXFRISorJly2rQoEFKS0uz5k2cOFGLFi3S559/bu1puvIx9+/fr44dO6p06dJq3Lix4uLiXPKcACgchB0AJUaZMmXUokULrV692mqLjY1V586d1bp1a6t9//79OnTokBV2rvbJJ59o4sSJeuWVV7Rx40ZVrlxZc+fOteaPGjVKDz74oLp27apjx47p2LFjatWqlTX/hRde0KhRo7Rlyxbddttteuihh3Tp0qVCWmsAN4qwA6BE6dixo7WXZefOnUpLS9Mdd9yhdu3aWe2xsbHy9fXVnXfemeMyZs6cqUGDBmnQoEGqU6eOpkyZovr161vz/f395efnJx8fH2tPk7e3tzV/1KhR6t69u2677TZNmjRJBw8e1L59+wptnQHcGMIOgBKlQ4cO2rNnj44dO6bY2Fi1adNGnp6eat++vVPYadWqlXx8fHJcxq5duxQREeHUFhkZmecabr/9duvvypUrS5KOHz+ezzUBUFQIOwBKlNatW8vb21urV6/W6tWr1b59e0lSixYt9Mcff2j//v2KjY1Vp06dCq0GLy8v62+HwyFJyszMLLTHA3BjCDsAShQ/Pz9FREQoNjZWa9asUYcOHSRdDiB33nmn3nvvPR0+fPia43UkqV69eoqPj3dq27Bhg9Ntb29vZWRkuLx+AEWPsAOgxOnYsaM++ugjpaWlqWnTplZ7+/btNXv2bGsg87U8/fTT+te//qUFCxZoz549mjBhgnbs2OHUJywsTFu3btXu3bv1xx9/6OLFi4W2PgAKF2EHQInTsWNHnTlzRq1bt1apUv//cmHt27fXmTNnrFPUr6VPnz4aN26cRo8erWbNmungwYN6/PHHnfoMHjxYderUUfPmzVWxYkX98MMPhbY+AAqXwxhjirsIAACAwsKeHQAAYGuEHQAAYGuEHQAAYGuEHQAAYGuEHQAAYGuEHQAAYGuEHQAAYGuEHQAAYGuEHQAAYGuEHQAAYGuEHQAAYGuEHQAAYGv/D+/PKi0eVtw1AAAAAElFTkSuQmCC", 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", "text/plain": [ "
" ] @@ -998,7 +998,12 @@ "for i in [13]:\n", "#for i in range(19):\n", " #defining precision required for the trotterized circuit\n", + " lattice_size = 32\n", + " evolution_time=1000\n", + " trotter_order = 2\n", " energy_precision = 1e-3\n", + " extrapolated=True\n", + "\n", "\n", " figdir=\"Trotter/Figures/\"\n", " if not os.path.exists(figdir):\n", @@ -1007,7 +1012,8 @@ " if not os.path.exists(widthdir):\n", " os.makedirs(widthdir)\n", "\n", - " evolution_time=1000\n", + "\n", + "\n", " H_rucl = generate_rucl_hamiltonian(32, df_rucl.iloc[i], field_x=lambda s: 1/sqrt(6), field_y=lambda s: 1/sqrt(6), field_z=lambda s: -2/sqrt(6))\n", " H_rucl_pyliqtr = pyH(H_rucl)\n", " openfermion_hamiltonian_rucl = pyliqtr_hamiltonian_to_openfermion_qubit_operator(H_rucl_pyliqtr)\n", @@ -1015,13 +1021,19 @@ " rucl_name = f'Rucl_row_{i}_trotter'\n", " hash_uid = hashlib.sha256(rucl_name.encode('utf-8'))\n", " uid = hash_uid.hexdigest()\n", - " trotter_metadata = EstimateMetaData(\n", + "\n", + "\n", + " trotter_metadata = TrotterizationMetaData(\n", " id = uid,\n", " name=rucl_name,\n", " category='scientific',\n", - " size=f'lattice_size: 32',\n", + " size='lattice_size: {}'.format(lattice_size),\n", " task='Time-Dependent Dynamics',\n", - " implementations=f'trotterization, JT={evolution_time}, gate_synth_accuracy=1e-10, energy_precision={energy_precision}',\n", + " implementation='Trotterization',\n", + " evolution_time=evolution_time,\n", + " trotter_order=trotter_order,\n", + " energy_precision=energy_precision,\n", + " is_extrapolated=extrapolated,\n", " )\n", "\n", " print(f'Estimating RuCl row {i} using Trotterization')\n", @@ -1030,8 +1042,10 @@ " openfermion_hamiltonian=openfermion_hamiltonian_rucl,\n", " evolution_time=evolution_time,\n", " energy_precision=energy_precision,\n", + " trotter_order=trotter_order,\n", " outdir='Trotter/RuCl_circuits/',\n", " metadata=trotter_metadata,\n", + " is_extrapolated=extrapolated,\n", " hamiltonian_name=f'rucl_trotter_{i}',\n", " write_circuits=True\n", " )\n", @@ -1069,20 +1083,20 @@ "output_type": "stream", "text": [ "Estimating RuCl row 13 using QSP\n", - "Time to generate high level QSP circuit: 176.14209862499956 seconds\n", - " Time to decompose high level _PauliX circuit: 0.00016345900075975806 seconds \n", - " Time to transform decomposed _PauliX circuit to Clifford+T: 4.0083999920170754e-05 seconds\n", - " Time to decompose high level Rx circuit: 3.0375000278581865e-05 seconds \n", - " Time to transform decomposed Rx circuit to Clifford+T: 0.010096124999108724 seconds\n", - " Time to decompose high level UnitaryBlockEncode circuit: 23.286359624999022 seconds \n", - " Time to transform decomposed UnitaryBlockEncode circuit to Clifford+T: 189.8889178749996 seconds\n", - " Time to decompose high level Ry circuit: 0.19155120799950964 seconds \n", - " Time to transform decomposed Ry circuit to Clifford+T: 0.006916083000760409 seconds\n", - " Time to decompose high level _InverseCompositeGate circuit: 45.29211675000079 seconds \n", - " Time to transform decomposed _InverseCompositeGate circuit to Clifford+T: 184.61656849999963 seconds\n", - " Time to decompose high level Reflect circuit: 0.19982183299907774 seconds \n", - " Time to transform decomposed Reflect circuit to Clifford+T: 0.023435875000359374 seconds\n", - "Time to estimate RuCl row 13: 968.7507476669998 seconds\n", + "Time to generate high level QSP circuit: 106.46940012497362 seconds\n", + " Time to decompose high level _PauliX circuit: 7.374997949227691e-05 seconds \n", + " Time to transform decomposed _PauliX circuit to Clifford+T: 2.3500004317611456e-05 seconds\n", + " Time to decompose high level Rx circuit: 2.4666020181030035e-05 seconds \n", + " Time to transform decomposed Rx circuit to Clifford+T: 0.008130667032673955 seconds\n", + " Time to decompose high level UnitaryBlockEncode circuit: 25.91511416702997 seconds \n", + " Time to transform decomposed UnitaryBlockEncode circuit to Clifford+T: 150.9490537919919 seconds\n", + " Time to decompose high level Ry circuit: 0.10220795898931101 seconds \n", + " Time to transform decomposed Ry circuit to Clifford+T: 0.005874917027540505 seconds\n", + " Time to decompose high level _InverseCompositeGate circuit: 28.04190108302282 seconds \n", + " Time to transform decomposed _InverseCompositeGate circuit to Clifford+T: 135.57108429196524 seconds\n", + " Time to decompose high level Reflect circuit: 0.14782412501517683 seconds \n", + " Time to transform decomposed Reflect circuit to Clifford+T: 0.02132041600998491 seconds\n", + "Time to estimate RuCl row 13: 718.1651687499834 seconds\n", "\n", "\n" ] @@ -1093,27 +1107,35 @@ "for i in [13]:\n", "#for i in range(19):\n", " #defining precision required for the trotterized circuit\n", + " lattice_size=32\n", + " evolution_time=1000\n", + " nsteps=1000\n", " energy_precision = 1e-3\n", + "\n", " figdir=\"QSP/Figures/\"\n", " if not os.path.exists(figdir):\n", " os.makedirs(figdir)\n", " widthdir = \"QSP/Widths/\"\n", " if not os.path.exists(widthdir):\n", " os.makedirs(widthdir)\n", - " evolution_time=1000\n", - " H_rucl = generate_rucl_hamiltonian(32, df_rucl.iloc[i], field_x=lambda s: 1/sqrt(6), field_y=lambda s: 1/sqrt(6), field_z=lambda s: -2/sqrt(6))\n", + "\n", + " H_rucl = generate_rucl_hamiltonian(lattice_size, df_rucl.iloc[i], field_x=lambda s: 1/sqrt(6), field_y=lambda s: 1/sqrt(6), field_z=lambda s: -2/sqrt(6))\n", " H_rucl_pyliqtr = pyH(H_rucl)\n", " \n", " rucl_name = f'Rucl_row_{i}_qsp'\n", " hash_uid = hashlib.sha256(rucl_name.encode('utf-8'))\n", " uid = hash_uid.hexdigest()\n", - " qsp_metadata = EstimateMetaData(\n", + "\n", + " qsp_metadata = QSPMetaData(\n", " id=uid,\n", " name=rucl_name,\n", " category='scientific',\n", - " size=f'lattice_size: 32',\n", + " size='lattice_size: {}'.format(lattice_size),\n", " task='Time-Dependent Dynamics',\n", - " implementations='QSP, JT={evolution_time}, gate_synth_accuracy=1e-10, energy_precision={energy_precision}',\n", + " implementation='QSP',\n", + " evolution_time=evolution_time,\n", + " nsteps=nsteps,\n", + " energy_precision=energy_precision,\n", " )\n", " \n", " print(f'Estimating RuCl row {i} using QSP')\n", @@ -1122,7 +1144,7 @@ " qsp_high_level_rucl = estimate_qsp(\n", " pyliqtr_hamiltonian=H_rucl_pyliqtr,\n", " evolution_time=evolution_time,\n", - " numsteps=1000,\n", + " nsteps=nsteps,\n", " energy_precision=energy_precision,\n", " outdir='QSP/RuCl_circuits/',\n", " hamiltonian_name=f'rucl_qsp_{i}',\n", @@ -1273,7 +1295,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Total time to run notebook (only using the fastest row): 1445.9630092499992\n" + "Total time to run notebook (only using the fastest row): 1011.2058625000063\n" ] } ], @@ -1306,7 +1328,7 @@ ], "metadata": { "kernelspec": { - "display_name": "other_qca", + "display_name": "qc-apps", "language": "python", "name": "python3" }, @@ -1320,7 +1342,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.12.0" + "version": "3.11.10" } }, "nbformat": 4, From ff75ff383bd13c39f9837ed666c217fc1b34e535 Mon Sep 17 00:00:00 2001 From: gsgrattan Date: Tue, 5 Nov 2024 13:21:31 -0700 Subject: [PATCH 18/35] implemented saving a calculated number of trotter steps to the TrotterizationMetaData in estimate_trotter() --- src/qca/utils/algo_utils.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/qca/utils/algo_utils.py b/src/qca/utils/algo_utils.py index cdd01e2..d8966d6 100644 --- a/src/qca/utils/algo_utils.py +++ b/src/qca/utils/algo_utils.py @@ -126,7 +126,6 @@ def estimate_trotter( if not os.path.exists(outdir): os.makedirs(outdir) - #TODO: Modify MetaData object in this case if not nsteps: t0 = time.perf_counter() bounded_error = error_bound(list(openfermion_hamiltonian.get_operators()),tight=False) @@ -136,6 +135,7 @@ def estimate_trotter( t1 = time.perf_counter() elapsed = t1 - t0 print(f'Time to estimate number of trotter steps required ({nsteps}): {elapsed} seconds') + metadata.nsteps=nsteps t0 = time.perf_counter() term_ordering = find_hamiltonian_ordering(openfermion_hamiltonian) From 0d68f755159cd51542ee655353ca0e3fd29bdf9a Mon Sep 17 00:00:00 2001 From: github-actions <41898282+github-actions[bot]@users.noreply.github.com> Date: Tue, 5 Nov 2024 20:27:10 +0000 Subject: [PATCH 19/35] Updated pylint badge --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 17cda60..8a460a6 100644 --- a/README.md +++ b/README.md @@ -1,4 +1,4 @@ -![pylint](https://img.shields.io/badge/PyLint-9.42-yellow?logo=python&logoColor=white) +![pylint](https://img.shields.io/badge/PyLint-9.26-yellow?logo=python&logoColor=white) # Quantum Computing Application Specifications From c69c316e9e0494ac4e2f1c5075890cadac39c797 Mon Sep 17 00:00:00 2001 From: github-actions <41898282+github-actions[bot]@users.noreply.github.com> Date: Thu, 7 Nov 2024 16:04:55 +0000 Subject: [PATCH 20/35] Updated pylint badge --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index c3db08e..29f74e9 100644 --- a/README.md +++ b/README.md @@ -1,4 +1,4 @@ -![pylint](https://img.shields.io/badge/PyLint-9.29-yellow?logo=python&logoColor=white) +![pylint](https://img.shields.io/badge/PyLint-9.26-yellow?logo=python&logoColor=white) # Quantum Computing Application Specifications From 629ca0a9a28bf938e082737cb2101c0a7a5fea3e Mon Sep 17 00:00:00 2001 From: gsgrattan Date: Thu, 7 Nov 2024 19:54:55 -0700 Subject: [PATCH 21/35] removed 'implementation' flag from metadata objects and their implementations --- notebooks/DickeModelExample.ipynb | 2 -- .../HighTemperatureSuperConductorExample.ipynb | 8 +++----- notebooks/MagneticLattices.ipynb | 18 +++++++----------- notebooks/PhotosynthesisExample.ipynb | 3 +-- notebooks/RuClExample.ipynb | 2 -- scripts/DickeModel.py | 1 - scripts/HTSC-one-band-RE.py | 1 - scripts/HTSC-three-band-RE.py | 1 - scripts/HTSC-two-band-RE.py | 1 - scripts/RuCl-RE.py | 2 -- scripts/TavisCummingsModel.py | 3 +-- src/qca/utils/utils.py | 6 ++---- 12 files changed, 14 insertions(+), 34 deletions(-) diff --git a/notebooks/DickeModelExample.ipynb b/notebooks/DickeModelExample.ipynb index f6d7abf..2e19fa3 100644 --- a/notebooks/DickeModelExample.ipynb +++ b/notebooks/DickeModelExample.ipynb @@ -325,7 +325,6 @@ " is_extrapolated=extrapolate,\n", " bits_precision = bits_precision_dicke,\n", " nsteps=trotter_steps_dicke,\n", - " implementation='GSEE'\n", " )" ] }, @@ -478,7 +477,6 @@ " is_extrapolated=extrapolate,\n", " bits_precision = bits_precision_tavis_cummings,\n", " nsteps=trotter_steps_tavis_cummings,\n", - " implementation='GSEE'\n", ")" ] }, diff --git a/notebooks/HighTemperatureSuperConductorExample.ipynb b/notebooks/HighTemperatureSuperConductorExample.ipynb index e420ff6..0021be3 100644 --- a/notebooks/HighTemperatureSuperConductorExample.ipynb +++ b/notebooks/HighTemperatureSuperConductorExample.ipynb @@ -169,7 +169,7 @@ " is_extrapolated=extrapolate,\n", " bits_precision=bits_precision_one_band,\n", " nsteps=trotter_steps_one_band,\n", - " implementation=\"GSEE\"\n", + "\n", ")" ] }, @@ -526,7 +526,7 @@ " is_extrapolated=extrapolate,\n", " bits_precision=bits_precision_current_limit,\n", " nsteps=trotter_steps_current_limit,\n", - " implementation=\"GSEE\"\n", + "\n", ")\n", "\n", "metadata_ideal = GSEEMetaData(\n", @@ -540,7 +540,7 @@ " is_extrapolated=extrapolate,\n", " bits_precision=bits_precision_ideal,\n", " nsteps=trotter_steps_ideal,\n", - " implementation=\"GSEE\"\n", + "\n", ")" ] }, @@ -1055,7 +1055,6 @@ " is_extrapolated=extrapolate,\n", " bits_precision=bits_precision_current_limit,\n", " nsteps=trotter_steps_current_limit,\n", - " implementation=\"GSEE\"\n", ")\n", "\n", "metadata_ideal = GSEEMetaData(\n", @@ -1069,7 +1068,6 @@ " is_extrapolated=extrapolate,\n", " bits_precision=bits_precision_ideal,\n", " nsteps=trotter_steps_ideal,\n", - " implementation=\"GSEE\"\n", ")" ] }, diff --git a/notebooks/MagneticLattices.ipynb b/notebooks/MagneticLattices.ipynb index 4951a0b..dea3038 100644 --- a/notebooks/MagneticLattices.ipynb +++ b/notebooks/MagneticLattices.ipynb @@ -230,7 +230,6 @@ " category='scientific',\n", " size=f'lattice_size: {square_lattice_size}',\n", " task='Time Dependent Dynamics',\n", - " implementation='QSP',\n", " evolution_time=evolution_time,\n", " nsteps=numsteps,\n", " energy_precision=required_precision\n", @@ -243,7 +242,6 @@ " category='scientific',\n", " size=f'lattice_size: {square_lattice_size}',\n", " task='Time Dependent Dynamics',\n", - " implementation='QSP',\n", " evolution_time=evolution_time,\n", " nsteps=numsteps,\n", " energy_precision=required_precision\n", @@ -257,7 +255,6 @@ " category='scientific',\n", " size=f'lattice_size: {square_lattice_size}',\n", " task='Time Dependent Dynamics',\n", - " implementation='QSP',\n", " evolution_time=evolution_time,\n", " nsteps=numsteps,\n", " energy_precision=required_precision\n", @@ -482,7 +479,7 @@ " category='scientific',\n", " size=f'lattice_size: {lattice_size_kitaev}',\n", " task='Time Dependent Dynamics',\n", - " implementation='QSP',\n", + "\n", " evolution_time=evolution_time,\n", " nsteps=numsteps,\n", " energy_precision=required_precision\n", @@ -586,8 +583,7 @@ " name='directional_triangle_qsp',\n", " category='scientific',\n", " size=f'lattice_size: {lattice_size_directional_triangle}',\n", - " task='Time Dependent Dynamics',\n", - " implementation='QSP',\n", + " task='Time Dependent Dynamics', \n", " evolution_time=evolution_time,\n", " nsteps=numsteps,\n", " energy_precision=required_precision\n", @@ -644,7 +640,7 @@ " category='scientific',\n", " size=f'lattice_size: {square_lattice_size}',\n", " task='Time Dependent Dynamics',\n", - " implementation='trotterization',\n", + "\n", " evolution_time=evolution_time,\n", " trotter_order= 2,\n", " is_extrapolated=extrapolate,\n", @@ -658,7 +654,7 @@ " category='scientific',\n", " size=f'lattice_size: {square_lattice_size}',\n", " task='Time Dependent Dynamics',\n", - " implementation='trotterization',\n", + "\n", " evolution_time=evolution_time,\n", " trotter_order= 2,\n", " is_extrapolated=extrapolate,\n", @@ -672,7 +668,7 @@ " category='scientific',\n", " size=f'lattice_size: {square_lattice_size}',\n", " task='Time Dependent Dynamics',\n", - " implementation='trotterization',\n", + "\n", " evolution_time=evolution_time,\n", " trotter_order= 2,\n", " is_extrapolated=extrapolate,\n", @@ -686,7 +682,7 @@ " category='scientific',\n", " size=f'lattice_size: {square_lattice_size}',\n", " task='Time Dependent Dynamics',\n", - " implementation='trotterization',\n", + "\n", " evolution_time=evolution_time,\n", " trotter_order= 2,\n", " is_extrapolated=extrapolate,\n", @@ -700,7 +696,7 @@ " category='scientific',\n", " size=f'lattice_size: {square_lattice_size}',\n", " task='Time Dependent Dynamics',\n", - " implementation='trotterization',\n", + "\n", " evolution_time=evolution_time,\n", " trotter_order= 2,\n", " is_extrapolated=extrapolate,\n", diff --git a/notebooks/PhotosynthesisExample.ipynb b/notebooks/PhotosynthesisExample.ipynb index 5af087d..87f633b 100644 --- a/notebooks/PhotosynthesisExample.ipynb +++ b/notebooks/PhotosynthesisExample.ipynb @@ -709,8 +709,7 @@ " name=f'Co2O9H12_{idx}',\n", " category='scientific',\n", " size=f'{n_qubits} qubits',\n", - " task='Ground State Energy Estimation',\n", - " implementation='GSEE',\n", + " task='Ground State Energy Estimation', \n", " bits_precision=bits_precision,\n", " evolution_time=ev_time,\n", " is_extrapolated=extrapolate,\n", diff --git a/notebooks/RuClExample.ipynb b/notebooks/RuClExample.ipynb index a9663e2..0aba2e1 100644 --- a/notebooks/RuClExample.ipynb +++ b/notebooks/RuClExample.ipynb @@ -1029,7 +1029,6 @@ " category='scientific',\n", " size='lattice_size: {}'.format(lattice_size),\n", " task='Time-Dependent Dynamics',\n", - " implementation='Trotterization',\n", " evolution_time=evolution_time,\n", " trotter_order=trotter_order,\n", " energy_precision=energy_precision,\n", @@ -1132,7 +1131,6 @@ " category='scientific',\n", " size='lattice_size: {}'.format(lattice_size),\n", " task='Time-Dependent Dynamics',\n", - " implementation='QSP',\n", " evolution_time=evolution_time,\n", " nsteps=nsteps,\n", " energy_precision=energy_precision,\n", diff --git a/scripts/DickeModel.py b/scripts/DickeModel.py index 035e544..12ceeb7 100644 --- a/scripts/DickeModel.py +++ b/scripts/DickeModel.py @@ -72,7 +72,6 @@ def main(args): is_extrapolated=is_extrapolated, bits_precision = bits_precision_dicke, nsteps=trotter_steps_dicke, - implementation='GSEE' ) print('Estimating Dicke') diff --git a/scripts/HTSC-one-band-RE.py b/scripts/HTSC-one-band-RE.py index b87a8cc..a203ec4 100644 --- a/scripts/HTSC-one-band-RE.py +++ b/scripts/HTSC-one-band-RE.py @@ -68,7 +68,6 @@ def main(args): is_extrapolated=is_extrapolated, bits_precision=bits_precision, nsteps=trotter_steps, - implementation="GSEE" ) print('Estimating one_band') diff --git a/scripts/HTSC-three-band-RE.py b/scripts/HTSC-three-band-RE.py index e51656b..3e36169 100644 --- a/scripts/HTSC-three-band-RE.py +++ b/scripts/HTSC-three-band-RE.py @@ -76,7 +76,6 @@ def main(args): is_extrapolated=is_extrapolated, bits_precision=bits_precision, nsteps=trotter_steps, - implementation="GSEE" ) print('Estimating Circuit Resources') diff --git a/scripts/HTSC-two-band-RE.py b/scripts/HTSC-two-band-RE.py index 2c0d42d..42f0cbd 100644 --- a/scripts/HTSC-two-band-RE.py +++ b/scripts/HTSC-two-band-RE.py @@ -71,7 +71,6 @@ def main(args): is_extrapolated=is_extrapolated, bits_precision=bits_precision, nsteps=trotter_steps, - implementation="GSEE" ) print('Estimating Circuit Resources') diff --git a/scripts/RuCl-RE.py b/scripts/RuCl-RE.py index d3cc05d..9dc5653 100644 --- a/scripts/RuCl-RE.py +++ b/scripts/RuCl-RE.py @@ -212,7 +212,6 @@ def generate_rucl_re( trotter_order = trotter_order, energy_precision=energy_precision, is_extrapolated=is_extrapolated, - implementation = 'Trotterization' ) estimate_trotter( openfermion_hamiltonian=openfermion_hamiltonian_rucl, @@ -237,7 +236,6 @@ def generate_rucl_re( evolution_time = evolution_time, nsteps = nsteps, energy_precision=energy_precision, - implementation = 'Trotterization' ) estimate_qsp( diff --git a/scripts/TavisCummingsModel.py b/scripts/TavisCummingsModel.py index 98b5496..dff897a 100644 --- a/scripts/TavisCummingsModel.py +++ b/scripts/TavisCummingsModel.py @@ -68,8 +68,7 @@ def main(args): trotter_order = trotter_order_tavis_cummings, is_extrapolated=is_extrapolated, bits_precision = bits_precision_tavis_cummings, - nsteps=trotter_steps_tavis_cummings, - implementation='GSEE' + nsteps=trotter_steps_tavis_cummings, ) print('Estimating tavis_cummings') diff --git a/src/qca/utils/utils.py b/src/qca/utils/utils.py index 4195a45..a8d1a90 100644 --- a/src/qca/utils/utils.py +++ b/src/qca/utils/utils.py @@ -33,7 +33,7 @@ class GSEEMetaData(EstimateMetaData): trotter_order: int nsteps: int is_extrapolated: bool - implementation: str = "GSEE" + #TODO: Potentially add gate_synth_accuracy to the following two dataclasses @dataclass class TrotterizationMetaData(EstimateMetaData): @@ -41,15 +41,13 @@ class TrotterizationMetaData(EstimateMetaData): trotter_order: int energy_precision: float is_extrapolated:bool - nsteps: int=None - implementation: str= "Trotterization" + nsteps: int=None @dataclass class QSPMetaData(EstimateMetaData): evolution_time: float #NOTE: This is JT in the current implementation nsteps: int energy_precision: float - implementation:str = "QSP" def count_gates(cpt_circuit: cirq.AbstractCircuit) -> int: count = 0 From 799a3fdcbed238614851a1362309577d1ad6622b Mon Sep 17 00:00:00 2001 From: gsgrattan Date: Thu, 7 Nov 2024 20:20:07 -0700 Subject: [PATCH 22/35] Resolved issue with misunderstanding the usage of circuit_extimate, also fixed the convention with using objects as arguments and defaulting them to None --- src/qca/utils/algo_utils.py | 9 ++++----- src/qca/utils/utils.py | 4 ++-- 2 files changed, 6 insertions(+), 7 deletions(-) diff --git a/src/qca/utils/algo_utils.py b/src/qca/utils/algo_utils.py index d8966d6..8d7c8ef 100644 --- a/src/qca/utils/algo_utils.py +++ b/src/qca/utils/algo_utils.py @@ -37,7 +37,7 @@ def estimate_qsp( nsteps:int, energy_precision:float, outdir:str, - metadata: QSPMetaData = None, + metadata: QSPMetaData | None=None, algo_name: str = 'QSP', hamiltonian_name:str='hamiltonian', write_circuits:bool=False, @@ -114,7 +114,7 @@ def estimate_trotter( energy_precision: float, outdir:str, trotter_order: int = 2, - metadata: TrotterizationMetaData=None, + metadata: TrotterizationMetaData | None=None, algo_name: str = 'TrotterStep', hamiltonian_name:str='hamiltonian', is_extrapolated: bool = True, @@ -196,7 +196,7 @@ def gsee_resource_estimation( precision_order:int, bits_precision:int, phase_offset:float, - metadata:GSEEMetaData=None, + metadata:GSEEMetaData | None =None, algo_name='GSEE', circuit_name:str='Hamiltonian', is_extrapolated:bool=False, @@ -227,8 +227,7 @@ def gsee_resource_estimation( numsteps=nsteps, algo_name=algo_name, include_nested_resources=include_nested_resources, - bits_precision=bits_precision, - is_extrapolated=is_extrapolated, + bits_precision=bits_precision, write_circuits=write_circuits ) outfile = f'{outdir}{circuit_name}_re.json' diff --git a/src/qca/utils/utils.py b/src/qca/utils/utils.py index a8d1a90..08418fa 100644 --- a/src/qca/utils/utils.py +++ b/src/qca/utils/utils.py @@ -48,6 +48,7 @@ class QSPMetaData(EstimateMetaData): evolution_time: float #NOTE: This is JT in the current implementation nsteps: int energy_precision: float + implementation:str = "QSP" def count_gates(cpt_circuit: cirq.AbstractCircuit) -> int: count = 0 @@ -241,7 +242,6 @@ def circuit_estimate( algo_name: str, include_nested_resources:bool, bits_precision:int=1, - is_extrapolated:bool=False, write_circuits:bool = False ) -> dict: if not os.path.exists(outdir): @@ -291,7 +291,7 @@ def circuit_estimate( subcircuit_name = subcircuit_counts[gate][2] resource_estimate = gen_resource_estimate( subcircuit, - is_extrapolated=is_extrapolated, + is_extrapolated=False, circ_occurences=occurence, bits_precision=bits_precision ) From a2a4da8013799755b36be881bf6bba938230fc3b Mon Sep 17 00:00:00 2001 From: gsgrattan Date: Thu, 7 Nov 2024 20:34:59 -0700 Subject: [PATCH 23/35] Renamed TrotterizationMetaData -> TrotterMetaData --- notebooks/MagneticLattices.ipynb | 12 ++++++------ notebooks/RuClExample.ipynb | 4 ++-- scripts/RuCl-RE.py | 4 ++-- src/qca/utils/algo_utils.py | 4 ++-- src/qca/utils/utils.py | 2 +- 5 files changed, 13 insertions(+), 13 deletions(-) diff --git a/notebooks/MagneticLattices.ipynb b/notebooks/MagneticLattices.ipynb index dea3038..3f688c8 100644 --- a/notebooks/MagneticLattices.ipynb +++ b/notebooks/MagneticLattices.ipynb @@ -66,7 +66,7 @@ "from networkx.classes.graph import Graph\n", "from networkx.generators.lattice import hexagonal_lattice_graph\n", "\n", - "from qca.utils.utils import plot_histogram, QSPMetaData, TrotterizationMetaData \n", + "from qca.utils.utils import plot_histogram, QSPMetaData, TrotterMetaData \n", "from qca.utils.algo_utils import estimate_qsp, estimate_trotter\n", "from qca.utils.hamiltonian_utils import (nx_triangle_lattice, flatten_nx_graph,\n", " generate_square_hamiltonian, pyliqtr_hamiltonian_to_openfermion_qubit_operator,\n", @@ -634,7 +634,7 @@ "\n", "extrapolate=True\n", "\n", - "trotter_square_metadata = TrotterizationMetaData(\n", + "trotter_square_metadata = TrotterMetaData(\n", " id=uid,\n", " name='square_lattice_trotter',\n", " category='scientific',\n", @@ -648,7 +648,7 @@ ")\n", "uid += 1\n", "\n", - "trotter_triangle_metadata = TrotterizationMetaData(\n", + "trotter_triangle_metadata = TrotterMetaData(\n", " id=uid,\n", " name='square_lattice_trotter',\n", " category='scientific',\n", @@ -662,7 +662,7 @@ ")\n", "uid += 1\n", "\n", - "trotter_cubic_metadata = TrotterizationMetaData(\n", + "trotter_cubic_metadata = TrotterMetaData(\n", " id=uid,\n", " name='square_lattice_trotter',\n", " category='scientific',\n", @@ -676,7 +676,7 @@ ")\n", "uid += 1\n", "\n", - "trotter_kitaev_metadata = TrotterizationMetaData(\n", + "trotter_kitaev_metadata = TrotterMetaData(\n", " id=uid,\n", " name='square_lattice_trotter',\n", " category='scientific',\n", @@ -690,7 +690,7 @@ ")\n", "uid += 1\n", "\n", - "trotter_directional_triangle_metadata = TrotterizationMetaData(\n", + "trotter_directional_triangle_metadata = TrotterMetaData(\n", " id=uid,\n", " name='square_lattice_trotter',\n", " category='scientific',\n", diff --git a/notebooks/RuClExample.ipynb b/notebooks/RuClExample.ipynb index 0aba2e1..58c8323 100644 --- a/notebooks/RuClExample.ipynb +++ b/notebooks/RuClExample.ipynb @@ -72,7 +72,7 @@ "from qca.utils.algo_utils import estimate_qsp, estimate_trotter\n", "from pyLIQTR.gate_decomp.cirq_transforms import clifford_plus_t_direct_transform\n", "\n", - "from qca.utils.utils import plot_histogram, gen_resource_estimate, re_as_json, EstimateMetaData, QSPMetaData, TrotterizationMetaData\n", + "from qca.utils.utils import plot_histogram, gen_resource_estimate, re_as_json, EstimateMetaData, QSPMetaData, TrotterMetaData\n", "from qca.utils.hamiltonian_utils import flatten_nx_graph, assign_hexagon_labels, pyliqtr_hamiltonian_to_openfermion_qubit_operator" ] }, @@ -1023,7 +1023,7 @@ " uid = hash_uid.hexdigest()\n", "\n", "\n", - " trotter_metadata = TrotterizationMetaData(\n", + " trotter_metadata = TrotterMetaData(\n", " id = uid,\n", " name=rucl_name,\n", " category='scientific',\n", diff --git a/scripts/RuCl-RE.py b/scripts/RuCl-RE.py index 9dc5653..808e6fd 100644 --- a/scripts/RuCl-RE.py +++ b/scripts/RuCl-RE.py @@ -6,7 +6,7 @@ from networkx import Graph from pandas import DataFrame from networkx.generators.lattice import hexagonal_lattice_graph -from qca.utils.utils import TrotterizationMetaData, QSPMetaData +from qca.utils.utils import TrotterMetaData, QSPMetaData from qca.utils.algo_utils import estimate_trotter, estimate_qsp from qca.utils.hamiltonian_utils import ( flatten_nx_graph, @@ -200,7 +200,7 @@ def generate_rucl_re( is_extrapolated=True - trotter_metadata = TrotterizationMetaData( + trotter_metadata = TrotterMetaData( id=f'{time.time_ns()}', name=f'RuCl_row_{rucl_idx}', category='scientific', diff --git a/src/qca/utils/algo_utils.py b/src/qca/utils/algo_utils.py index 8d7c8ef..c1eff5b 100644 --- a/src/qca/utils/algo_utils.py +++ b/src/qca/utils/algo_utils.py @@ -27,7 +27,7 @@ estimate_cpt_resources, EstimateMetaData, GSEEMetaData, - TrotterizationMetaData, + TrotterMetaData, QSPMetaData ) @@ -114,7 +114,7 @@ def estimate_trotter( energy_precision: float, outdir:str, trotter_order: int = 2, - metadata: TrotterizationMetaData | None=None, + metadata: TrotterMetaData | None=None, algo_name: str = 'TrotterStep', hamiltonian_name:str='hamiltonian', is_extrapolated: bool = True, diff --git a/src/qca/utils/utils.py b/src/qca/utils/utils.py index 08418fa..f360ca2 100644 --- a/src/qca/utils/utils.py +++ b/src/qca/utils/utils.py @@ -36,7 +36,7 @@ class GSEEMetaData(EstimateMetaData): #TODO: Potentially add gate_synth_accuracy to the following two dataclasses @dataclass -class TrotterizationMetaData(EstimateMetaData): +class TrotterMetaData(EstimateMetaData): evolution_time: float #NOTE: This is JT in the current implementation trotter_order: int energy_precision: float From 6560c79d3204af37e00008111ef7157739bf0b65 Mon Sep 17 00:00:00 2001 From: gsgrattan Date: Wed, 13 Nov 2024 10:50:59 -0700 Subject: [PATCH 24/35] Resolved Hardcoding issue --- scripts/HTSC-one-band-RE.py | 4 ---- 1 file changed, 4 deletions(-) diff --git a/scripts/HTSC-one-band-RE.py b/scripts/HTSC-one-band-RE.py index a203ec4..956cc5b 100644 --- a/scripts/HTSC-one-band-RE.py +++ b/scripts/HTSC-one-band-RE.py @@ -29,10 +29,6 @@ def main(args): ham = of.fermi_hubbard(lattice_size, lattice_size, tunneling=tunneling, coulomb=coulomb, periodic=False) #returns an aperiodic fermionic hamiltonian - #TODO: Fix this Hardcoding - trotter_order = 2 - trotter_steps = 1 #Using one trotter step for a strict lower bound with this method - #this scales the circuit depth proportional to 2 ^ bits_precision bits_precision = estimate_bits_precision(error_precision) From a39064219461ffda236171f3f9fed5c799419f4e Mon Sep 17 00:00:00 2001 From: gsgrattan Date: Wed, 13 Nov 2024 12:03:21 -0700 Subject: [PATCH 25/35] Fixed bug where directory storing the pathway datafiles was not specified, added -d/--directory argument to specify --- scripts/AP-RE.py | 18 +++++++++++++----- 1 file changed, 13 insertions(+), 5 deletions(-) diff --git a/scripts/AP-RE.py b/scripts/AP-RE.py index 84aceec..03a4edd 100644 --- a/scripts/AP-RE.py +++ b/scripts/AP-RE.py @@ -20,6 +20,13 @@ def grab_arguments() -> Namespace: help='Factor to reduce the active space', default=10 ) + parser.add_argument( + '-d', + '--directory', + type=str, + help='Directoty with pathway datafiles.', + default='./data/' + ) args = parser.parse_args() return args @@ -70,26 +77,27 @@ def grab_molecular_hamiltonians_pool( pid = os.getpid() args = grab_arguments() active_space_reduc = args.active_space_reduction + pathway_directory= args.directory pathways = [ pathway_info( pathway=[27, 1, 14, 15, 16, 24, 25, 26], - fname='water_oxidation_Co2O9H12.xyz' + fname=pathway_directory+'water_oxidation_Co2O9H12.xyz' ), pathway_info( pathway=[3, 1, 14, 15, 16, 20, 21, 22, 23], - fname='water_oxidation_Co2O9H12.xyz' + fname=pathway_directory+'water_oxidation_Co2O9H12.xyz' ), pathway_info( pathway=[2, 1, 14, 15, 16, 17, 18, 19], - fname='water_oxidation_Co2O9H12.xyz' + fname=pathway_directory+'water_oxidation_Co2O9H12.xyz' ), pathway_info( pathway=[5, 10, 28, 29, 30, 31, 32, 33], - fname='water_oxidation_Co2O9H12.xyz' + fname=pathway_directory+'water_oxidation_Co2O9H12.xyz' ) ] coords_pathways = [ - load_pathway(pathway.fname, pathway.pathway) for pathway in pathways + load_pathway(pathway_directory+pathway.fname, pathway.pathway) for pathway in pathways ] molecular_hamiltonians = grab_molecular_hamiltonians_pool( active_space_reduc=active_space_reduc, From 53ba80c9a1b010a06b98c03ea610e811f030718f Mon Sep 17 00:00:00 2001 From: gsgrattan Date: Wed, 13 Nov 2024 14:04:31 -0700 Subject: [PATCH 26/35] mend --- scripts/AP-RE.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/scripts/AP-RE.py b/scripts/AP-RE.py index 03a4edd..67f7e09 100644 --- a/scripts/AP-RE.py +++ b/scripts/AP-RE.py @@ -97,7 +97,7 @@ def grab_molecular_hamiltonians_pool( ) ] coords_pathways = [ - load_pathway(pathway_directory+pathway.fname, pathway.pathway) for pathway in pathways + load_pathway(pathway.fname, pathway.pathway) for pathway in pathways ] molecular_hamiltonians = grab_molecular_hamiltonians_pool( active_space_reduc=active_space_reduc, From 11c0bfed5567634c3760ca922d3f5cf403c3c68b Mon Sep 17 00:00:00 2001 From: gsgrattan Date: Wed, 13 Nov 2024 15:01:45 -0700 Subject: [PATCH 27/35] removed TODO, functionality needs to be implemented in another PR --- scripts/AP-RE.py | 1 - 1 file changed, 1 deletion(-) diff --git a/scripts/AP-RE.py b/scripts/AP-RE.py index 67f7e09..84abbe8 100644 --- a/scripts/AP-RE.py +++ b/scripts/AP-RE.py @@ -4,7 +4,6 @@ from concurrent.futures import ThreadPoolExecutor, as_completed, ProcessPoolExecutor from qca.utils.chemistry_utils import load_pathway, generate_electronic_hamiltonians, gsee_molecular_hamiltonian -#TODO: Integrate the MetaData classes into this functionality @dataclass class pathway_info: From 39d238e7e1df4f2b9105a2c75f6a3143534e7b07 Mon Sep 17 00:00:00 2001 From: github-actions <41898282+github-actions[bot]@users.noreply.github.com> Date: Wed, 13 Nov 2024 22:03:56 +0000 Subject: [PATCH 28/35] Updated pylint badge --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 29f74e9..806f8fd 100644 --- a/README.md +++ b/README.md @@ -1,4 +1,4 @@ -![pylint](https://img.shields.io/badge/PyLint-9.26-yellow?logo=python&logoColor=white) +![pylint](https://img.shields.io/badge/PyLint-9.22-yellow?logo=python&logoColor=white) # Quantum Computing Application Specifications From 0e8f986a1a92fbda447565e9e9b6d03ec0569c4c Mon Sep 17 00:00:00 2001 From: gsgrattan Date: Fri, 15 Nov 2024 09:02:46 -0700 Subject: [PATCH 29/35] Made suggested changes to utils.py --- src/qca/utils/utils.py | 14 +++++--------- 1 file changed, 5 insertions(+), 9 deletions(-) diff --git a/src/qca/utils/utils.py b/src/qca/utils/utils.py index f360ca2..034a3b2 100644 --- a/src/qca/utils/utils.py +++ b/src/qca/utils/utils.py @@ -15,7 +15,6 @@ from pyLIQTR.utils.utils import count_T_gates from pyLIQTR.gate_decomp.cirq_transforms import clifford_plus_t_direct_transform -#TODO: Figure out issue with partent class with default values and child classes don't have them @dataclass class EstimateMetaData: id: str @@ -23,8 +22,10 @@ class EstimateMetaData: category: str size: str task: str - value_per_circuit: float=field(default=None, kw_only=True) - repetitions_per_application: int=field(default=None, kw_only=True) + is_extrapolated: bool=field(default=False, kw_only=True) + gate_synth_accuracy: float| str | None=field(default='1e-10',kw_only=True) + value_per_circuit: float | None=field(default=None, kw_only=True) + repetitions_per_application: int | None=field(default=None, kw_only=True) @dataclass class GSEEMetaData(EstimateMetaData): @@ -32,15 +33,11 @@ class GSEEMetaData(EstimateMetaData): bits_precision: int trotter_order: int nsteps: int - is_extrapolated: bool - -#TODO: Potentially add gate_synth_accuracy to the following two dataclasses @dataclass class TrotterMetaData(EstimateMetaData): evolution_time: float #NOTE: This is JT in the current implementation trotter_order: int energy_precision: float - is_extrapolated:bool nsteps: int=None @dataclass @@ -48,7 +45,6 @@ class QSPMetaData(EstimateMetaData): evolution_time: float #NOTE: This is JT in the current implementation nsteps: int energy_precision: float - implementation:str = "QSP" def count_gates(cpt_circuit: cirq.AbstractCircuit) -> int: count = 0 @@ -138,7 +134,7 @@ def gen_resource_estimate( from the circuit and then write it to disk. The function also returns the resource dictionary if the user needs it. - trotter_steps is a flag denoting if the circuit was estimated through trotterization. If so, the + total_steps is a flag denoting if the circuit was estimated through trotterization. If so, the user should specify the number of steps required. ''' num_qubits = len(cpt_circuit.all_qubits()) From 4e763a122dd05f0feaab0e696b8a11e335104c28 Mon Sep 17 00:00:00 2001 From: gsgrattan Date: Fri, 15 Nov 2024 09:16:00 -0700 Subject: [PATCH 30/35] made suggested changes to algo_utils.py --- src/qca/utils/algo_utils.py | 13 +++++-------- 1 file changed, 5 insertions(+), 8 deletions(-) diff --git a/src/qca/utils/algo_utils.py b/src/qca/utils/algo_utils.py index c1eff5b..a813018 100644 --- a/src/qca/utils/algo_utils.py +++ b/src/qca/utils/algo_utils.py @@ -38,7 +38,6 @@ def estimate_qsp( energy_precision:float, outdir:str, metadata: QSPMetaData | None=None, - algo_name: str = 'QSP', hamiltonian_name:str='hamiltonian', write_circuits:bool=False, include_nested_resources:bool=True @@ -62,7 +61,7 @@ def estimate_qsp( circuit=qsp_circuit, outdir=outdir, numsteps=nsteps, - algo_name=algo_name, + algo_name='QSP', write_circuits=write_circuits, include_nested_resources=include_nested_resources ) @@ -115,11 +114,10 @@ def estimate_trotter( outdir:str, trotter_order: int = 2, metadata: TrotterMetaData | None=None, - algo_name: str = 'TrotterStep', hamiltonian_name:str='hamiltonian', is_extrapolated: bool = True, write_circuits:bool=False, - nsteps:int=None, + nsteps:int|None=None, include_nested_resources:bool=True ) -> Circuit: @@ -135,7 +133,7 @@ def estimate_trotter( t1 = time.perf_counter() elapsed = t1 - t0 print(f'Time to estimate number of trotter steps required ({nsteps}): {elapsed} seconds') - metadata.nsteps=nsteps + metadata.nsteps=nsteps t0 = time.perf_counter() term_ordering = find_hamiltonian_ordering(openfermion_hamiltonian) @@ -176,7 +174,7 @@ def estimate_trotter( cpt_circuit=cpt_trotter, outdir=outdir, is_extrapolated=is_extrapolated, - algo_name= algo_name, + algo_name= 'TrotterStep', trotter_steps=nsteps, include_nested_resources=include_nested_resources ) @@ -197,7 +195,6 @@ def gsee_resource_estimation( bits_precision:int, phase_offset:float, metadata:GSEEMetaData | None =None, - algo_name='GSEE', circuit_name:str='Hamiltonian', is_extrapolated:bool=False, include_nested_resources:bool=True, @@ -225,7 +222,7 @@ def gsee_resource_estimation( circuit=pe_circuit, outdir=outdir, numsteps=nsteps, - algo_name=algo_name, + algo_name='GSEE', include_nested_resources=include_nested_resources, bits_precision=bits_precision, write_circuits=write_circuits From 08c1b1f6af4ec427ba470d4b4d6bea7a683ed403 Mon Sep 17 00:00:00 2001 From: gsgrattan Date: Fri, 15 Nov 2024 14:21:52 -0700 Subject: [PATCH 31/35] implemented gate_synth_accuracy into the EstimateMetaData class and passed it into all calls of clifford_plus_t_direct_transform --- src/qca/utils/algo_utils.py | 11 +++++++++-- src/qca/utils/utils.py | 7 ++++--- 2 files changed, 13 insertions(+), 5 deletions(-) diff --git a/src/qca/utils/algo_utils.py b/src/qca/utils/algo_utils.py index a813018..1895286 100644 --- a/src/qca/utils/algo_utils.py +++ b/src/qca/utils/algo_utils.py @@ -57,11 +57,14 @@ def estimate_qsp( elapsed = t1 - t0 print(f'Time to generate high level QSP circuit: {elapsed} seconds') outfile = f'{outdir}{hamiltonian_name}_re.json' + + gate_synth_accuracy=metadata.gate_synth_accuracy logical_re = circuit_estimate( circuit=qsp_circuit, outdir=outdir, numsteps=nsteps, algo_name='QSP', + gate_synth_accuracy=gate_synth_accuracy, write_circuits=write_circuits, include_nested_resources=include_nested_resources ) @@ -120,7 +123,7 @@ def estimate_trotter( nsteps:int|None=None, include_nested_resources:bool=True ) -> Circuit: - + if not os.path.exists(outdir): os.makedirs(outdir) @@ -150,10 +153,11 @@ def estimate_trotter( elapsed = t1 - t0 print(f'Time to generate trotter circuit from openfermion: {elapsed} seconds') + gate_synth_accuracy = metadata.gate_synth_accuracy qasm_str_trotter = open_fermion_to_qasm(count_qubits(openfermion_hamiltonian), trotter_circuit_of) trotter_circuit_qasm = qasm_import.circuit_from_qasm(qasm_str_trotter) t0 = time.perf_counter() - cpt_trotter = clifford_plus_t_direct_transform(trotter_circuit_qasm) + cpt_trotter = clifford_plus_t_direct_transform(circuit=trotter_circuit_qasm, gate_precision=gate_synth_accuracy) t1 = time.perf_counter() elapsed = t1-t0 print(f'Time to generate a clifford + T circuit from trotter circuit: {elapsed} seconds') @@ -217,6 +221,8 @@ def gsee_resource_estimation( gse_circuit.generate_circuit() pe_circuit = gse_circuit.pe_circuit + gate_synth_accuracy=metadata.gate_synth_accuracy + t0 = time.perf_counter() logical_re = circuit_estimate( circuit=pe_circuit, @@ -224,6 +230,7 @@ def gsee_resource_estimation( numsteps=nsteps, algo_name='GSEE', include_nested_resources=include_nested_resources, + gate_synth_accuracy=gate_synth_accuracy, bits_precision=bits_precision, write_circuits=write_circuits ) diff --git a/src/qca/utils/utils.py b/src/qca/utils/utils.py index 034a3b2..827720f 100644 --- a/src/qca/utils/utils.py +++ b/src/qca/utils/utils.py @@ -23,7 +23,7 @@ class EstimateMetaData: size: str task: str is_extrapolated: bool=field(default=False, kw_only=True) - gate_synth_accuracy: float| str | None=field(default='1e-10',kw_only=True) + gate_synth_accuracy: int | float = field(default=10,kw_only=True) value_per_circuit: float | None=field(default=None, kw_only=True) repetitions_per_application: int | None=field(default=None, kw_only=True) @@ -237,6 +237,7 @@ def circuit_estimate( numsteps: int, algo_name: str, include_nested_resources:bool, + gate_synth_accuracy: int | float = 10, bits_precision:int=1, write_circuits:bool = False ) -> dict: @@ -257,7 +258,7 @@ def circuit_estimate( decomposed_elapsed = t1-t0 print(f' Time to decompose high level {gate_type_name} circuit: {decomposed_elapsed} seconds ') t0 = time.perf_counter() - cpt_circuit = clifford_plus_t_direct_transform(decomposed_circuit) + cpt_circuit = clifford_plus_t_direct_transform(circuit = decomposed_circuit, gate_precision=gate_synth_accuracy) t1 = time.perf_counter() cpt_elapsed = t1-t0 print(f' Time to transform decomposed {gate_type_name} circuit to Clifford+T: {cpt_elapsed} seconds') @@ -330,7 +331,7 @@ def circuit_estimate( main_estimates['Logical_Abstract']['subcircuit_info'][algo_name]['subcircuit_info'][op_key] = op[op_key] return main_estimates - +#TODO: Implement method to properly format gate_synth_accuracy def re_as_json(main_estimate:dict, outdir:str) -> None: with open(outdir, 'w') as f: json.dump(main_estimate, f, From df863c09c191588fdd4784cc758250da82fb4767 Mon Sep 17 00:00:00 2001 From: gsgrattan Date: Fri, 15 Nov 2024 15:08:18 -0700 Subject: [PATCH 32/35] made changes to python notebooks --- notebooks/HighTemperatureSuperConductorExample.ipynb | 8 ++++---- notebooks/MagneticLattices.ipynb | 12 ++++++------ notebooks/RuClExample.ipynb | 6 +++--- 3 files changed, 13 insertions(+), 13 deletions(-) diff --git a/notebooks/HighTemperatureSuperConductorExample.ipynb b/notebooks/HighTemperatureSuperConductorExample.ipynb index 0021be3..a28aa96 100644 --- a/notebooks/HighTemperatureSuperConductorExample.ipynb +++ b/notebooks/HighTemperatureSuperConductorExample.ipynb @@ -1045,7 +1045,7 @@ "source": [ "metadata_current_limit = GSEEMetaData(\n", " id=3000,\n", - " name='FermiHubbard_Two_Band_Current_Limit`',\n", + " name='FermiHubbard_Three_Band_Current_Limit`',\n", " category='scientific',\n", " size=f'{6}x{7}',\n", " task='Ground State Energy Estimation',\n", @@ -1059,7 +1059,7 @@ "\n", "metadata_ideal = GSEEMetaData(\n", " id=4000,\n", - " name='FermiHubbard_Two_Band_Ideal',\n", + " name='FermiHubbard_Three_Band_Ideal',\n", " category='scientific',\n", " size=f'{20}x{20}',\n", " task='Ground State Energy Estimation',\n", @@ -1121,7 +1121,7 @@ " precision_order=1,\n", " bits_precision=bits_precision_current_limit,\n", " phase_offset=phase_offset_current_limit,\n", - " circuit_name='two_band_current_limit',\n", + " circuit_name='three_band_current_limit',\n", " is_extrapolated=extrapolate,\n", " metadata=metadata_current_limit,\n", " write_circuits=True\n", @@ -1139,7 +1139,7 @@ " precision_order=1,\n", " bits_precision=bits_precision_ideal,\n", " phase_offset=phase_offset_ideal,\n", - " circuit_name='two_band_ideal',\n", + " circuit_name='three_band_ideal',\n", " is_extrapolated=extrapolate,\n", " metadata=metadata_ideal,\n", " write_circuits=True\n", diff --git a/notebooks/MagneticLattices.ipynb b/notebooks/MagneticLattices.ipynb index 3f688c8..9dd6497 100644 --- a/notebooks/MagneticLattices.ipynb +++ b/notebooks/MagneticLattices.ipynb @@ -238,9 +238,9 @@ "\n", "triangle_lattice_metadata = QSPMetaData(\n", " id=uid,\n", - " name='square_lattice',\n", + " name='triangle_lattice',\n", " category='scientific',\n", - " size=f'lattice_size: {square_lattice_size}',\n", + " size=f'lattice_size: {triangle_lattice_size}',\n", " task='Time Dependent Dynamics',\n", " evolution_time=evolution_time,\n", " nsteps=numsteps,\n", @@ -251,9 +251,9 @@ "\n", "cubic_lattice_metadata = QSPMetaData(\n", " id=uid,\n", - " name='square_lattice',\n", + " name='cubic_lattice',\n", " category='scientific',\n", - " size=f'lattice_size: {square_lattice_size}',\n", + " size=f'lattice_size: {cubic_lattice_size}',\n", " task='Time Dependent Dynamics',\n", " evolution_time=evolution_time,\n", " nsteps=numsteps,\n", @@ -650,7 +650,7 @@ "\n", "trotter_triangle_metadata = TrotterMetaData(\n", " id=uid,\n", - " name='square_lattice_trotter',\n", + " name='triangle_lattice_trotter',\n", " category='scientific',\n", " size=f'lattice_size: {square_lattice_size}',\n", " task='Time Dependent Dynamics',\n", @@ -664,7 +664,7 @@ "\n", "trotter_cubic_metadata = TrotterMetaData(\n", " id=uid,\n", - " name='square_lattice_trotter',\n", + " name='cubic_lattice_trotter',\n", " category='scientific',\n", " size=f'lattice_size: {square_lattice_size}',\n", " task='Time Dependent Dynamics',\n", diff --git a/notebooks/RuClExample.ipynb b/notebooks/RuClExample.ipynb index 58c8323..39b19a8 100644 --- a/notebooks/RuClExample.ipynb +++ b/notebooks/RuClExample.ipynb @@ -1014,7 +1014,7 @@ "\n", "\n", "\n", - " H_rucl = generate_rucl_hamiltonian(32, df_rucl.iloc[i], field_x=lambda s: 1/sqrt(6), field_y=lambda s: 1/sqrt(6), field_z=lambda s: -2/sqrt(6))\n", + " H_rucl = generate_rucl_hamiltonian(lattice_size, df_rucl.iloc[i], field_x=lambda s: 1/sqrt(6), field_y=lambda s: 1/sqrt(6), field_z=lambda s: -2/sqrt(6))\n", " H_rucl_pyliqtr = pyH(H_rucl)\n", " openfermion_hamiltonian_rucl = pyliqtr_hamiltonian_to_openfermion_qubit_operator(H_rucl_pyliqtr)\n", " \n", @@ -1027,7 +1027,7 @@ " id = uid,\n", " name=rucl_name,\n", " category='scientific',\n", - " size='lattice_size: {}'.format(lattice_size),\n", + " size=f'lattice_size: {lattice_size}',\n", " task='Time-Dependent Dynamics',\n", " evolution_time=evolution_time,\n", " trotter_order=trotter_order,\n", @@ -1129,7 +1129,7 @@ " id=uid,\n", " name=rucl_name,\n", " category='scientific',\n", - " size='lattice_size: {}'.format(lattice_size),\n", + " size=f'lattice_size: {lattice_size}',\n", " task='Time-Dependent Dynamics',\n", " evolution_time=evolution_time,\n", " nsteps=nsteps,\n", From b2b6df8be1881af36c733bbdd57ce2bdd6aecdea Mon Sep 17 00:00:00 2001 From: gsgrattan Date: Fri, 15 Nov 2024 15:39:38 -0700 Subject: [PATCH 33/35] Formatting changes to scripts --- scripts/AP-RE.py | 8 ++++---- scripts/RuCl-RE.py | 14 +++++++++----- 2 files changed, 13 insertions(+), 9 deletions(-) diff --git a/scripts/AP-RE.py b/scripts/AP-RE.py index 84abbe8..4d4af3a 100644 --- a/scripts/AP-RE.py +++ b/scripts/AP-RE.py @@ -80,19 +80,19 @@ def grab_molecular_hamiltonians_pool( pathways = [ pathway_info( pathway=[27, 1, 14, 15, 16, 24, 25, 26], - fname=pathway_directory+'water_oxidation_Co2O9H12.xyz' + fname=f'{pathway_directory}water_oxidation_Co2O9H12.xyz' ), pathway_info( pathway=[3, 1, 14, 15, 16, 20, 21, 22, 23], - fname=pathway_directory+'water_oxidation_Co2O9H12.xyz' + fname=f'{pathway_directory}water_oxidation_Co2O9H12.xyz' ), pathway_info( pathway=[2, 1, 14, 15, 16, 17, 18, 19], - fname=pathway_directory+'water_oxidation_Co2O9H12.xyz' + fname='{pathway_directory}water_oxidation_Co2O9H12.xyz' ), pathway_info( pathway=[5, 10, 28, 29, 30, 31, 32, 33], - fname=pathway_directory+'water_oxidation_Co2O9H12.xyz' + fname='{pathway_directory}water_oxidation_Co2O9H12.xyz' ) ] coords_pathways = [ diff --git a/scripts/RuCl-RE.py b/scripts/RuCl-RE.py index 808e6fd..66cb5cd 100644 --- a/scripts/RuCl-RE.py +++ b/scripts/RuCl-RE.py @@ -180,6 +180,12 @@ def generate_rucl_re( evolution_time:float, df_rucl:DataFrame, outdir:str) -> None: + + nsteps = 1500000 + gate_synth_accuracy = 10 + trotter_order = 2 + is_extrapolated=True + if not os.path.exists(outdir): os.makedirs(outdir) for rucl_idx in range(len(df_rucl)): @@ -194,10 +200,7 @@ def generate_rucl_re( openfermion_hamiltonian_rucl = pyliqtr_hamiltonian_to_openfermion_qubit_operator(H_rucl_pyliqtr) #TODO: Handle the Hardcoding here - I just pulled the hardcoded values up from internal functions and centralized them here - nsteps = 1500000 - gate_synth_accuracy = 1e-10 - trotter_order = 2 - is_extrapolated=True + trotter_metadata = TrotterMetaData( @@ -207,6 +210,7 @@ def generate_rucl_re( size=f'lattice_size: {lattice_size}', task='Time-Dependent Dynamics', + gate_synth_accuracy=gate_synth_accuracy, evolution_time = evolution_time, nsteps = nsteps, trotter_order = trotter_order, @@ -220,7 +224,7 @@ def generate_rucl_re( metadata=trotter_metadata, outdir=outdir, trotter_order=trotter_order, - + gate_synth_accuracy=gate_synth_accuracy, hamiltonian_name=f'trotter_rucl_size_{lattice_size}_row_{rucl_idx}', nsteps=nsteps, is_extrapolated=is_extrapolated From 2b04a8f87428af9139047539e39ca8723ae76431 Mon Sep 17 00:00:00 2001 From: gsgrattan Date: Fri, 15 Nov 2024 16:24:33 -0700 Subject: [PATCH 34/35] Removed depreciated passing of gate_synth_accuracy of gate_synth_accuracy as an argument to estimate_trotter --- scripts/RuCl-RE.py | 1 - 1 file changed, 1 deletion(-) diff --git a/scripts/RuCl-RE.py b/scripts/RuCl-RE.py index 491a463..4cb400a 100644 --- a/scripts/RuCl-RE.py +++ b/scripts/RuCl-RE.py @@ -221,7 +221,6 @@ def generate_rucl_re( metadata=trotter_metadata, outdir=outdir, trotter_order=trotter_order, - gate_synth_accuracy=gate_synth_accuracy, hamiltonian_name=f'trotter_rucl_size_{lattice_size}_row_{rucl_idx}', nsteps=nsteps, is_extrapolated=is_extrapolated From c6d2ec195e53c9e99e5f9c7b1006efa5706aa151 Mon Sep 17 00:00:00 2001 From: github-actions <41898282+github-actions[bot]@users.noreply.github.com> Date: Fri, 15 Nov 2024 23:26:36 +0000 Subject: [PATCH 35/35] Updated pylint badge --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 806f8fd..266dd11 100644 --- a/README.md +++ b/README.md @@ -1,4 +1,4 @@ -![pylint](https://img.shields.io/badge/PyLint-9.22-yellow?logo=python&logoColor=white) +![pylint](https://img.shields.io/badge/PyLint-9.21-yellow?logo=python&logoColor=white) # Quantum Computing Application Specifications