We construct neural networks that work for any Lie group and maintain
gauge covariance, enabling smooth, invertible gauge field transformations.
We implement these transformations for 4D SU(3) lattice gauge fields
and explore their use in HMC.
We focus on developing loss functions and optimizing the transformations.
We show the effects on HMC's molecular dynamics and discuss
the scalability of the approach.
Volume 453 -
The 40th International Symposium on Lattice Field Theory (LATTICE2023) -
Algorithms and Artificial Intelligence
Neural Network Gauge Field Transformation for 4D SU(3) gauge fields
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Pre-published on:
October 11, 2024
Published on:
November 06, 2024
Abstract
DOI: https://doi.org/10.22323/1.453.0040
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Copyright owned by the author(s) under the term of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Copyright owned by the author(s) under the term of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.