Symmetry-invariant quantum machine learning force fields

Symmetry-invariant quantum machine learning force fields

Machine learning techniques are essential tools to compute efficient, yet accurate, force fields for atomistic simulations. This approach has recently been extended to incorporate quantum computational methods, making use of variational quantum learning models to predict potential energy surfaces an...

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Bibliographic Details
Main Authors: Isabel Nha Minh Le, Oriel Kiss, Julian Schuhmacher, Ivano Tavernelli, Francesco Tacchino
Format: Article
Language:English
Published: IOP Publishing 2025-01-01
Series:New Journal of Physics
Subjects:
molecular force fields
geometric quantum machine learning
equivariant quantum neural networks
Online Access:https://doi.org/10.1088/1367-2630/adad0c

Internet

https://doi.org/10.1088/1367-2630/adad0c

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