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Diffusion models for lattice gauge field simulations

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arxiv 2410.19602 v1 pith:PG2MOBHA submitted 2024-10-25 hep-lat

Diffusion models for lattice gauge field simulations

classification hep-lat
keywords gaugediffusionlatticemodelscouplinginversemodelsimulations
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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We develop diffusion models for lattice gauge theories which build on the concept of stochastic quantization. This framework is applied to $U(1)$ gauge theory in $1+1$ dimensions. We show that a model trained at one small inverse coupling can be effectively transferred to larger inverse coupling without encountering issues related to topological freezing, i.e., the model can generate configurations corresponding to different couplings by introducing the Boltzmann factors as physics conditions, while maintaining the correct physical distributions without any additional training. This demonstrates the potential of physics-conditioned diffusion models for efficient and flexible lattice gauge theory simulations.

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Cited by 3 Pith papers

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

  1. Diffusion Models for Sampling Near Criticality in Lattice Field Theories

    hep-lat 2026-07 accept novelty 6.0

    Fully convolutional diffusion models trained on small lattices transfer to unseen larger volumes for 2D/3D phi^4 sampling across phases, matching or beating same-size training on most observables.

  2. 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.

  3. Improvement of Heatbath Algorithm in LFT using Generative models

    physics.comp-ph 2023-08 unverdicted novelty 6.0

    Generative models learn conditional local distributions conditioned on neighbors and action parameters to improve Heatbath proposals for continuous-variable lattice models without target samples.