Applications of Machine Learning to Lattice Quantum Field Theory

There is great potential to apply machine learning in the area of numerical lattice quantum field theory, but full exploitation of that potential will require new strategies. In this white paper for the Snowmass community planning process, we discuss the unique requirements of machine learning for l...

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Bibliographic Details
Published in:arXiv.org 2022-02
Main Authors: Boyda, Denis, Calì, Salvatore, eman, Sam, Funcke, Lena, Hackett, Daniel C, Lin, Yin, Aarts, Gert, Andrei Alexandru, Xiao-Yong, Jin, Lucini, Biagio, Shanahan, Phiala E
Format: Article
Language:English
Subjects:
Community planning
Field theory
Machine learning
Quantum field theory
Quantum theory
Online Access:Get full text
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Summary:There is great potential to apply machine learning in the area of numerical lattice quantum field theory, but full exploitation of that potential will require new strategies. In this white paper for the Snowmass community planning process, we discuss the unique requirements of machine learning for lattice quantum field theory research and outline what is needed to enable exploration and deployment of this approach in the future.
ISSN:2331-8422