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Estimation of Thermodynamic Observables in Lattice Field Theories with Deep Generative Models
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Estimation of Thermodynamic Observables in Lattice Field Theories with Deep Generative Models
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In this work, we demonstrate that applying deep generative machine learning models for lattice field theory is a promising route for solving problems where Markov Chain Monte Carlo (MCMC) methods are problematic. More specifically, we show that generative models can be used to estimate the absolute value of the free energy, which is in contrast to existing MCMC-based methods which are limited to only estimate free energy differences. We demonstrate the effectiveness of the proposed method for two-dimensional $\phi^4$ theory and compare it to MCMC-based methods in detailed numerical experiments.
Forward citations
Cited by 7 Pith papers
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Higher-order hopping-parameter expansion by human-AI collaboration
Trie-based algorithms evaluate the κ^8, κ^10 and κ^12 terms of Tr ln M on SU(Nc) configurations at costs of roughly 20, 460 and 8900 staple evaluations, verified against a reference implementation.
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Diffusion Models for Sampling Near Criticality in Lattice Field Theories
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.
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Higher-order hopping-parameter expansion by human-AI collaboration
Trie-based algorithms evaluate HPE coefficients through κ^12 on SU(Nc) configurations at roughly 20, 460, and 8900 staple costs, verified against a reference implementation.
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Scaling flow-based approaches for topology sampling in $\mathrm{SU}(3)$ gauge theory
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.
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Higher-order hopping-parameter expansion by human-AI collaboration
Trie-structured algorithms compute κ^8 to κ^12 terms in the hopping expansion of Tr ln M at costs scaling from 20x to 8900x a staple, verified by direct comparison to a reference calculation.
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Intrinsic Width of the Flux Tube as a tool to explore confining mechanisms in Lattice Gauge Theories
Lattice data on the intrinsic width of SU(2) flux tubes in 2+1D distinguish confining models, favoring dual superconductor at low T but with length-dependent Ginzburg-Landau parameter.
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Topological Susceptibility and QCD at Finite Theta Angle
A pedagogical review summarizing analytic predictions and recent lattice results for theta-dependence and topological susceptibility in QCD.
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