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Learning Trivializing Gradient Flows for Lattice Gauge Theories

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arxiv 2212.08469 v2 pith:SAF4MEXU submitted 2022-12-16 hep-lat

Learning Trivializing Gradient Flows for Lattice Gauge Theories

classification hep-lat
keywords latticelearningparametersapproachexistingmodeltheoriestheory
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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We propose a unifying approach that starts from the perturbative construction of trivializing maps by L\"uscher and then improves on it by learning. The resulting continuous normalizing flow model can be implemented using common tools of lattice field theory and requires several orders of magnitude fewer parameters than any existing machine learning approach. Specifically, our model can achieve competitive performance with as few as 14 parameters while existing deep-learning models have around 1 million parameters for $SU(3)$ Yang--Mills theory on a $16^2$ lattice. This has obvious consequences for training speed and interpretability. It also provides a plausible path for scaling machine-learning approaches toward realistic theories.

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Cited by 4 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

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

    hep-lat 2026-04 unverdicted novelty 7.0

    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.

  2. Diffusion model for SU(N) gauge theories

    hep-lat 2026-05 unverdicted novelty 6.0

    Implicit score matching trains diffusion models that successfully sample SU(3) Wilson gauge configurations on lattices, with a Hamiltonian-dynamics corrector needed for strong coupling.

  3. Scaling flow-based approaches for topology sampling in $\mathrm{SU}(3)$ gauge theory

    hep-lat 2025-10 unverdicted novelty 6.0

    Out-of-equilibrium simulations with open-to-periodic boundary switching plus a tailored stochastic normalizing flow enable efficient topology sampling in the continuum limit of four-dimensional SU(3) Yang-Mills theory.

  4. FLAG Review 2024

    hep-lat 2024-11 accept novelty 2.0

    The FLAG 2024 review provides updated averages of lattice QCD determinations for quark masses, decay constants, form factors, mixing parameters, and nucleon matrix elements.