i-PI 3.0: a flexible and efficient framework for advanced atomistic simulations

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Dades bibliogràfiques
Publicat a:	arXiv.org (Jul 10, 2024), p. n/a
Autor principal:	Litman, Yair
Altres autors:	Kapil, Venkat, Feldman, Yotam M Y, Tisi, Davide, Begušić, Tomislav, Fidanyan, Karen, Fraux, Guillaume, Higer, Jacob, Kellner, Matthias, Li, Tao E, Pós, Eszter S, Stocco, Elia, Trenins, George, Hirshberg, Barak, Rossi, Mariana, Ceriotti, Michele
Publicat:	Cornell University Library, arXiv.org
Matèries:	Simulation Algorithms Python Rapid prototyping Neural networks Modular structures Machine learning Electronic structure Computer simulation
Accés en línia:	Citation/Abstract Full text outside of ProQuest
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Descripció
Resum:	Atomic-scale simulations have progressed tremendously over the past decade, largely due to the availability of machine-learning interatomic potentials. These potentials combine the accuracy of electronic structure calculations with the ability to reach extensive length and time scales. The i-PI package facilitates integrating the latest developments in this field with advanced modeling techniques, thanks to a modular software architecture based on inter-process communication through a socket interface. The choice of Python for implementation facilitates rapid prototyping but can add computational overhead. In this new release, we carefully benchmarked and optimized i-PI for several common simulation scenarios, making such overhead negligible when i-PI is used to model systems up to tens of thousands of atoms using widely adopted machine learning interatomic potentials, such as Behler-Parinello, DeePMD and MACE neural networks. We also present the implementation of several new features, including an efficient algorithm to model bosonic and fermionic exchange, a framework for uncertainty quantification to be used in conjunction with machine-learning potentials, a communication infrastructure that allows deeper integration with electronic-driven simulations, and an approach to simulate coupled photon-nuclear dynamics in optical or plasmonic cavities.
ISSN:	2331-8422
DOI:	10.1063/5.0215869
Font:	Engineering Database