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Clinamen2: Functional-style evolutionary optimization in Python for atomistic structure searches ☆
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DOI：10.1016/j.cpc.2023.109065.png)
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Abstract
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Clinamen2 is a versatile functional-style Python implementation of the covariance matrix adaptation evolution strategy (CMA-ES) utilizing Cholesky decomposition. On top of a problem-agnostic core algorithm, the software package offers a suite of utilities and library code enabling applications to important atomistic structure searches. Features include massively distributed computation and the BI-Population restart scheme. This article details the general code structure and introduces examples that illustrate some relevant applications for the materials science and chemistry worlds, including interfacing to density-functional-theory codes and machine-learned surrogate models. The functional design renders the code modular and adaptable, and makes the creation of interfaces to other atomistic software straightforward.
Keywords:
CMA-ES
Optimization
Python
Atomistic calculations
Structure search
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