1.0 version is released. To install:
pip install CrysFieldExplorer
Import the main modules:
from CrysFieldExplorer import CrysFieldExplorer as crs
from CrysFieldExplorer import Optimization as opt
from CrysFieldExplorer import Visulization as vis
CrysFieldExplorer is a fast-converging Python package for optimizing crystal field parameters.
It supports calculation of a list of common rare earth ions. The program consists of three major modules: CrysfieldExplorer(main), Optimization and Visulization. Detailed tutorials will be uploaded soon.
The novalty of CrysFieldExplorer is it adopts a new loss function using theory of characteristic polynomials. By adopting this loss function it can globaly optimize the CEF hamiltonian with Neutron + any other experimental data and does not rely much on accurate starting value, which is usually estimated from point charge models.
A comparsion of the new Spectrum-Characteristic loss (
The details of this program can be found at https://scripts.iucr.org/cgi-bin/paper?S1600576723005897.
A comparison of the new loss function
This repo is organized with two types of examples corresponding to two types of optimization methods, Particle Swarm Optimization (PSO) and Covariance Matrix Adaptation Evolution Strategy (CMA-ES) used in conjunction with $L_{spectrum}. Generally speaking, when dealing with < 8 CEF parameters, PSO is a good choice for accuracy and for >=8 CEF parameters CMA-ES has shown significant gain in optimizing speed. In both types of examples the codes are desgined with being able to run parallel using mpi4py in mind.
The Yb2Ti2O7 is a classical example with 6 CEF parameters, traditional algorithms requires estimation of point charge model to provide insight. With CrysFieldExplorer, it can search large parameter phase space and provide a cluster of solutions of all 6 CEF parameters.
From these solutions it can produce excellent agreement between physical measured data and theoretical predictions.
