v1.11.2

Enhancements:

• Update the introduction to tensor contraction docs
• Improve efficiency of 1D structured contractions when default optimize is used.

Bug fixes:

• fixes for MPS and MPO constructors when L=1, (#314)
• tensor splitting with absorb="left" now correctly marks left indices.
• tn.isel: fix bug when value could not be compared to string "r"
• truncated svd, make n_chi comparison more robust to different backends

Full Changelog: v1.11.1...v1.11.2

v1.11.1

Enhancements:

• add create_bond to tensor_canonize_bond and tensor_compress_bond for optionally creating a new bond between two tensors if they don't already share one. Add as a flag to TensorNetwork1DFlat.compress and related functions (#294).
• add ensure_bonds_exist for ensuring that all bonds in a 1D flat tensor network exist. Use this in the permute_arrays methods and optionally in the expand_bond_dimension method.
• tn.draw(): permit empty network, and allow color=True to automatically color all tags.
• tn.add_tag: add a record: Optional[dict] kwarg, to allow for easy rewinding of temporary tags without tracking the actual networks.
• add qu.plot as a quick wrapper for calling matplotlib.pyplot.plot with the quimb style.
• quimb.schematic: add zorder_delta kwarg for fine adjustments to layering of objects in approximately the same position.
• operatorbuilder: big performance improvements and fixes for building matrix representations including Z2 symmetry. Add default symmetry and sector options that can be overridden at build time. Add lazy (slow, matrix free) 'apply' method. Add pauli_decompose transformation. Add experimental PEPO builder for nearest neighbor operators. Add unit tests.

Bug fixes:

• Fix TensorNetwork2D.compute_plaquette_environments for mode="zipup" and other boundary contraction methods that use the generic 1D compression algorithms.
• parse_openqasm2_str allow custom gate names to start with the word gate (#312).
• MatrixProductState.gate_with_mpo: fix bug to do with inplace argument (#313).

Full Changelog: v1.11.0...v1.11.1

v1.11.0

Breaking Changes

• move belief propagation to quimb.tensor.belief_propagation
• calling tn.contract() when an non-zero value has been accrued into tn.exponent now automatically re-absorbs that exponent.
• binary tensor operations that would previously have errored now will align and broadcast

Enhancements:

• Tensor: make binary operations (+, -, *, /, **) automatically align and broadcast indices. This would previously error.
• MatrixProductState.measure: add a seed kwarg
• belief propagation, implement DIIS (direct inversion in the iterative subspace)
• belief propagation, unify various aspects such as message normalization and distance.
• belief propagation, add a plot method.
• belief propagation, add a contract_every option.
• HV1BP: vectorize both contraction and message initialization
• add qu.plot_multi_series_zoom for plotting multiple series with a zoomed inset, useful for various convergence plots such as BP
• add info option to tn.gauge_all_simple for tracking extra information such as number of iterations and max gauge diffs
• Tensor.gate: add transposed option
• TensorNetwork.contract: add strip_exponent option for return the mantissa and exponent (log10) separately. Compatible with contract_tags, contract_cumulative, contract_compressed sub modes.
• tensor_split: add matrix_svals option, if True any returned singular values are put into the diagonal of a matrix (by default, False, they are returned as a vector).
• add Tensor.new_ind_pair_diag for expanding an existing index into a pair of new indices, such that the diagonal of the new tensor on those indices is the old tensor.
• TNOptimizer: add 'cautious' ADAM
• TensorNetwork.pop_tensor: allow tid or tags to be specified.
• add an example notebook for converting hyper tensor networks to normal tensor networks, for approximate contraction - https://quimb.readthedocs.io/en/latest/examples/ex_htn_to_tn_2d.html#example-htn-to-2d
• Add SX and SXDG gates by @kevinsung in #277
• Add XXPLUSYY and XXMINUSYY gates by @kevinsung in #279
• Added progbar to qsim, and openqasm2 by @edenian in #288
• quimb.experimental.operatorbuilder: fix MPO building for congested operators (#296 and #301), allow arbitrary dtype (#289). Fix building of sparse and matrix representations for non-translationally symmetric operators and operators with trivial (all identity) terms.

Bug fixes:

• fix MatrixProductState.measure for cupy backend arrays (#276).
• fix linalg.expm dispatch (#275)
• fix 'dm' 1d compress method for disconnected subgraphs
• fix docs source lookup in quimb.tensor module
• fix raw gate copying in Circuit (#285)

New Contributors

• @edenian made their first contribution in #288

Full Changelog: v1.10.0...v1.11.0

v1.10.0

Enhancements

• tensor network fitting: add method="tree" for when ansatz is a tree - tensor_network_fit_tree
• tensor network fitting: fix method="als" for complex dtype networks
• tensor network fitting: allow method="als" to use a iterative solver suited to much larger tensors, by default a custom conjugate gradient implementation.
• tensor_network_distance and fitting: support hyper indices explicitly via output_inds kwarg
• add tn.make_overlap and tn.overlap for computing the overlap between two tensor networks, $\langle O |T \rangle$, with explicit handling of outer indices to address hyper networks. Add output_inds to tn.norm and tn.make_norm also, as well as the squared kwarg.
• replace all numba based paralellism (prange and parallel vectorize) with explicit thread pool based parallelism. Should be more reliable and no need to set NUMBA_NUM_THREADS anymore. Remove env var QUIMB_NUMBA_PAR.
• Circuit: add dtype and convert_eager options. dtype specifies what the computation should be performed in. convert_eager specifies whether to apply this (and any to_backend calls) as soon as gates are applied (the default for MPS circuit simulation) or just prior to contraction (the default for exact contraction simulation).
• tn.full_simplify: add check_zero (by default set of "auto") option which explicitly checks for zero tensor norms when equalizing norms to avoid log10(norm) resulting in -inf or nan. Since it creates a data dependency that breaks e.g. jax tracing, it is optional.
• schematic.Drawing: add shorten kwarg to line drawing and curve drawing and examples to the docs.
• TensorNetwork: add .backend and .dtype_name properties.

PRs:

• Circuit: add default dtype and convert_eager options by @jcmgray in #273
• add fit(method="tree") and fix ALS for complex TNs by @jcmgray in #274

Full Changelog: v1.9.0...v1.10.0

v1.9.0

Breaking Changes

• renamed MatrixProductState.partial_trace and MatrixProductState.ptr to MatrixProductState.partial_trace_to_mpo to avoid confusion with other partial_trace methods that usually produce a dense matrix.

Enhancements:

• add Circuit.sample_gate_by_gate and related methods CircuitMPS.reordered_gates_dfs_clustered and CircuitMPS.get_qubit_distances for sampling a circuit using the 'gate by gate' method introduced in https://arxiv.org/abs/2112.08499.
• add Circuit.draw for drawing a very simple circuit schematic.
• Circuit: by default turn on simplify_equalize_norms and use a group_size=10 for sampling. This should result in faster and more stable sampling.
• Circuit: use numpy.random.default_rng for random number generation.
• add qtn.circ_a2a_rand for generating random all-to-all circuits.
• expose qtn.edge_coloring as top level function and allow layers to be returned grouped.
• add docstring for tn.contract_compressed and by default pick up important settings from the supplied contraction path optimizer (max_bond and compress_late)
• add Tensor.rand_reduce for randomly removing a tensor index by contracting a random vector into it. One can also supply the value "r" to isel selectors to use this.
• add fit-zipup and fit-projector shorthand methods to the general 1d tensor network compression function
• add MatrixProductState.compute_local_expectation for computing many local expectations for a MPS at once, to match the interface for this method elsewhere. These can either be computed via canonicalization (method="canonical"), or via explicit left and right environment contraction (method="envs")
• specialize CircuitMPS.local_expectation to make use of the MPS form.
• add PEPS.product_state for constructing a PEPS representing a product state.
• add PEPS.vacuum for constructing a PEPS representing the vacuum state $|000\ldots0\rangle$.
• add PEPS.zeros for constructing a PEPS whose entries are all zero.
• tn.gauge_all_simple: improve scheduling and add damping and touched_tids options.
• qtn.SimpleUpdateGen: add gauge difference update checking and tol and equilibrate settings. Update .plot() method. Default to a small cutoff.
• add psi.sample_configuration_cluster for sampling a tensor network using the simple update or cluster style environment approximation.
• add the new example doc Exploring circuit sampling with various methods

v1.8.4

What's Changed

• fix MPS sample handling of RNG seed by @kevinsung in #248
• fix bug in applying MPO lazily to MPS (#246)

New Contributors

• @kevinsung made their first contribution in #248

Full Changelog: v1.8.3...v1.8.4

v1.8.3

Enhancements:

• support for numpy v2.0 and scipy v1.14
• add MPS sampling: MatrixProductState.sample_configuration and MatrixProductState.sample (generating multiple samples) and use these for CircuitMPS.sample and CircuitPermMPS.sample.
• add basic plot method for [SimpleUpdate] classes
• add edges_1d_chain for generating 1D chain edges
• operatorbuilder: better coefficient placement for long range / non-local MPO building

Full Changelog: v1.8.2...v1.8.3

v1.8.2

Enhancements:

• TNOptimizer can now accept an arbitrary pytree (nested combination of dicts, lists, tuples, etc. with TensorNetwork, Tensor or raw array_like objects as the leaves) as the target object to optimize.
• TNOptimizer can now directly optimize Circuit objects, returning a new optimized circuit with updated parameters.
• Circuit: add .copy(), .get_params() and .set_params() interface methods.
• Update generic TN optimizer docs.
• add tn.gen_inds_loops for generating all loops of indices in a TN.
• add tn.gen_inds_connected for generating all connected sets of indices in a TN.
• make SVD fallback error catching more generic (by @mlxd in #238)
• fix some windows + numba CI issues.
• approx_spectral_function add plotting and tracking
• add dispatching to various tensor primitives to allow overriding

New Contributors

• @mlxd made their first contribution in #238

Full Changelog: v1.8.1...v1.8.2

v1.8.1

Enhancements:

• CircuitMPS now supports multi qubit gates, including arbitrary multi-controls (which are treated in a low-rank manner), and faster simulation via better orthogonality center tracking.
• add CircuitPermMPS, more docs here: https://quimb.readthedocs.io/en/latest/tensor-circuit-mps.html
• add MatrixProductState.gate_nonlocal for applying a gate, supplied as a raw matrix, to a non-local and arbitrary number of sites. The kwarg contract="nonlocal" can be used to force this method, or the new option "auto-mps" will select this method if the gate is non-local (#230)
• add MatrixProductState.gate_with_mpo for applying an MPO to an MPS, and immediately compressing back to MPS form using tensor_network_1d_compress
• add MatrixProductState.gate_with_submpo for applying an MPO acting only of a subset of sites to an MPS
• add MatrixProductOperator.from_dense for constructing MPOs from dense matrices, including an only subset of sites
• add MatrixProductOperator.fill_empty_sites for 'completing' an MPO which only has tensors on a subset of sites with (by default) identities
• MatrixProductState and MatrixProductOperator, now support the sites kwarg in common constructors, enabling the TN to act on a subset of the full L sites.
• add TensorNetwork.drape_bond_between for 'draping' an existing bond between two tensors through a third
• add Tensor.new_ind_pair_with_identity
• TN2D, TN3D and arbitrary geom classical partition function builders (TN_classical_partition_function_from_edges) now all support outputs= kwarg specifying non-marginalized variables
• add simple dense 1-norm belief propagation algorithm D1BP
• add qtn.enforce_1d_like for checking whether a tensor network is 1D-like, including automatically adding strings of identities between non-local bonds, expanding applicability of tensor_network_1d_compress
• add MatrixProductState.canonicalize as (by default non-inplace) version of canonize, to follow the pattern of other tensor network methods. canonize is now an alias for canonicalize_ [note trailing underscore].
• add MatrixProductState.left_canonicalize as (by default non-inplace) version of left_canonize, to follow the pattern of other tensor network methods. left_canonize is now an alias for left_canonicalize_ [note trailing underscore].
• add MatrixProductState.right_canonicalize as (by default non-inplace) version of right_canonize, to follow the pattern of other tensor network methods. right_canonize is now an alias for right_canonicalize_ [note trailing underscore].

Bug fixes:

• Circuit.apply_gate_raw: fix kwarg bug (#226) by @juliendrapeau
• fix for retrieving opt_einsum.PathInfo for single scalar contraction (#231).

New Contributors

• @juliendrapeau made their first contribution in #226

Full Changelog: v1.8.0...v1.8.1

v1.8.0

Breaking Changes

• all singular value renormalization is turned off by default
• TensorNetwork.compress_all now defaults to using some local gauging

Enhancements:

• add quimb.tensor.tensor_1d_compress.py with functions for compressing generic 1D tensor networks (with arbitrary local structure) using various methods. The methods are:

  • The 'direct' method: tensor_network_1d_compress_direct
  • The 'dm' (density matrix) method: tensor_network_1d_compress_dm
  • The 'zipup' method: tensor_network_1d_compress_zipup
  • The 'zipup-first' method: tensor_network_1d_compress_zipup_first
  • The 1 and 2 site 'fit' or sweeping method: tensor_network_1d_compress_fit
  • ... and some more niche methods for debugging and testing.

  And can be accessed via the unified function tensor_network_1d_compress. Boundary contraction in 2D can now utilize any of these methods.

• add quimb.tensor.tensor_arbgeom_compress.py with functions for compressing arbitrary geometry tensor networks using various methods. The methods are:

  • The 'local-early' method: tensor_network_ag_compress_local_early
  • The 'local-late' method: tensor_network_ag_compress_local_late
  • The 'projector' method: tensor_network_ag_compress_projector
  • The 'superorthogonal' method: tensor_network_ag_compress_superorthogonal
  • The 'l2bp' method: tensor_network_ag_compress_l2bp

  And can be accessed via the unified function tensor_network_ag_compress. 1D compression can also fall back to these methods.

• support PBC in tn2d.contract_hotrg, tn2d.contract_ctmrg, tn3d.contract_hotrg and the new function tn3d.contract_ctmrg.

• support PBC in gen_2d_bonds and gen_3d_bonds, with cyclic kwarg.

• support PBC in TN2D_rand_hidden_loop and TN3D_rand_hidden_loop, with cyclic kwarg.

• support PBC in the various base PEPS and PEPO construction methods.

• add tensor_network_apply_op_op for applying 'operator' TNs to 'operator' TNs.

• tweak tensor_network_apply_op_vec for applying 'operator' TNs to 'vector' or 'state' TNs.

• add tnvec.gate_with_op_lazy method for applying 'operator' TNs to 'vector' or 'state' TNs like $x \rightarrow A x$.

• add tnop.gate_upper_with_op_lazy method for applying 'operator' TNs to the upper indices of 'operator' TNs like $B \rightarrow A B$.

• add tnop.gate_lower_with_op_lazy method for applying 'operator' TNs to the lower indices of 'operator' TNs like $B \rightarrow B A$.

• add tnop.gate_sandwich_with_op_lazy method for applying 'operator' TNs to the upper and lower indices of 'operator' TNs like $B \rightarrow A B A^\dagger$.

• unify all TN summing routines into tensor_network_ag_sum, which allows summing any two tensor networks with matching site tags and outer indices, replacing specific MPS, MPO, PEPS, PEPO, etc. summing routines.

• add rand_symmetric_array, rand_tensor_symmetric TN2D_rand_symmetric for generating random symmetric arrays, tensors and 2D tensor networks.

Bug fixes:

• fix scipy sparse monkey patch for scipy>=1.13 (#222)
• fix autoblock bug where connected sectors were not being merged (#223)

Full Changelog: v1.7.3...v1.8.0