Gauge-equivariant flow models for sampling in lattice field theories with pseudofermions
High Energy Physics - Lattice
2023-05-26 v3 Machine Learning
Abstract
This work presents gauge-equivariant architectures for flow-based sampling in fermionic lattice field theories using pseudofermions as stochastic estimators for the fermionic determinant. This is the default approach in state-of-the-art lattice field theory calculations, making this development critical to the practical application of flow models to theories such as QCD. Methods by which flow-based sampling approaches can be improved via standard techniques such as even/odd preconditioning and the Hasenbusch factorization are also outlined. Numerical demonstrations in two-dimensional U(1) and SU(3) gauge theories with flavors of fermions are provided.
Keywords
Cite
@article{arxiv.2207.08945,
title = {Gauge-equivariant flow models for sampling in lattice field theories with pseudofermions},
author = {Ryan Abbott and Michael S. Albergo and Denis Boyda and Kyle Cranmer and Daniel C. Hackett and Gurtej Kanwar and Sébastien Racanière and Danilo J. Rezende and Fernando Romero-López and Phiala E. Shanahan and Betsy Tian and Julian M. Urban},
journal= {arXiv preprint arXiv:2207.08945},
year = {2023}
}
Comments
15 pages, 7 figures. v3: accepted version for publication. New appendix C