2026-10-13T13:33:52Z https://data.mendeley.com/oai

oai:data.mendeley.com/x7syr2txsd.1 2024-01-09T09:11:09Z

Ballantyne, John Clinamen2: Functional-style evolutionary optimization in Python for atomistic structure searches Mendeley Data 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. Atomic Physics Condensed Matter Physics Computational Physics Wanzenböck, Ralf Buchner, Florian Kovács, Péter Madsen, Georg K.H. Carrete, Jesús Dataset doi:10.17632/x7syr2txsd.1 oai:data.mendeley.com/x7syr2txsd.1 Apache License 2.0 http://www.apache.org/licenses/LICENSE-2.0 https://data.mendeley.com/datasets/x7syr2txsd 2024-01-09T09:11:09Z