Speaker
Dr
Sam Foreman
(Argonne National Laboratory)
Description
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.
| Topical area | Algorithms and Artificial Intelligence |
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