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.
Kanwar,Flow-based sampling for lattice field theories,PoSLATTICE2023(2024) 114 [2401.01297]
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Metadynamics bias potentials and volume-extrapolation strategies reduce integrated autocorrelation times of topological charge in lattice gauge theories.
Reviews approaches such as Lefschetz thimbles, complex Langevin dynamics, dual variables, tensor renormalization group, and machine learning to control the sign problem in lattice field theories.
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Metadynamics bias potentials and volume-extrapolation strategies reduce integrated autocorrelation times of topological charge in lattice gauge theories.
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Reviews approaches such as Lefschetz thimbles, complex Langevin dynamics, dual variables, tensor renormalization group, and machine learning to control the sign problem in lattice field theories.