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Multiscale Normalizing Flows for Gauge Theories

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arxiv 2404.10819 v1 pith:KVSKEQMJ submitted 2024-04-16 hep-lat

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

Scale separation is an important physical principle that has previously enabled algorithmic advances such as multigrid solvers. Previous work on normalizing flows has been able to utilize scale separation in the context of scalar field theories, but the principle has been largely unexploited in the context of gauge theories. This work gives an overview of a new method for generating gauge fields using hierarchical normalizing flow models. This method builds gauge fields from the outside in, allowing different parts of the model to focus on different scales of the problem. Numerical results are presented for $U(1)$ and $SU(3)$ gauge theories in 2, 3, and 4 spacetime dimensions.

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  1. Scalable Generative Sampling and Multilevel Estimation for Lattice Field Theories Near Criticality

    hep-lat 2026-04 unverdicted novelty 7.0 of 10

    A hierarchical generative model for critical lattice scalar field theories achieves orders-of-magnitude lower autocorrelation times than HMC while enabling exact multilevel Monte Carlo.

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