Papers
arxiv:2312.08936
MLMC: Machine Learning Monte Carlo for Lattice Gauge Theory
Published on Dec 14, 2023
Abstract
A trainable framework improves the efficiency of sampling gauge configurations from a 4D SU(3) lattice gauge theory using a generalized leapfrog integrator in molecular dynamics.
AI-generated summary
We present a trainable framework for efficiently generating gauge configurations, and discuss ongoing work in this direction. In particular, we consider the problem of sampling configurations from a 4D SU(3) lattice gauge theory, and consider a generalized leapfrog integrator in the molecular dynamics update that can be trained to improve sampling efficiency. Code is available online at https://github.com/saforem2/l2hmc-qcd.
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