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Progress in Normalizing Flows for 4d Gauge Theories

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arxiv 2502.00263 v1 pith:FBSYJRT4 submitted 2025-02-01 hep-lat

Ryan Abbott , Denis Boyda , Daniel C. Hackett , Gurtej Kanwar , Fernando Romero-López , Phiala E. Shanahan , Julian M. Urban This is my paper
classification hep-lat
keywords flowsnormalizingtheoriesgaugeprogressaccelerateactiveadvancements
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abstract

Normalizing flows have arisen as a tool to accelerate Monte Carlo sampling for lattice field theories. This work reviews recent progress in applying normalizing flows to 4-dimensional nonabelian gauge theories, focusing on two advancements: an architectural improvement referred to as learned active loops, and the application of correlated ensemble methods to QCD with $N_f=2$ dynamical fermions.

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Cited by 1 Pith paper

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  1. Machine learning for four-dimensional SU(3) lattice gauge theories

    hep-lat 2026-04 unverdicted novelty 3.0 of 10

    Machine learning generative models and renormalization-group neural networks are used to enhance gauge field sampling and learn fixed-point actions in 4D SU(3) lattice gauge theories, with presented scaling results to...

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