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Mitigating topological freezing using out-of-equilibrium simulations
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abstract
Motivated by the recently-established connection between Jarzynski's equality and the theoretical framework of Stochastic Normalizing Flows, we investigate a protocol relying on out-of-equilibrium lattice Monte Carlo simulations to mitigate the infamous computational problem of topological freezing. We test our proposal on $2d$ $\mathrm{CP}^{N-1}$ models and compare our results with those obtained adopting the Parallel Tempering on Boundary Conditions proposed by M. Hasenbusch, obtaining comparable performances. Our work thus sets the stage for future applications combining our Monte Carlo setup with machine learning techniques.
Forward citations
Cited by 3 Pith papers
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Parallel Tempered Metadynamics for full QCD
In N_f=2 staggered QCD at beta=1.15, PT-MetaD tunnels between topological sectors while RHMC remains frozen, yielding chi_top V = 0.127(33).
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Translation- and gauge-equivariant neural networks (L-CNNs) predict Wilson loops, topological charge, and flux observables with orders-of-magnitude lower error than symmetry-breaking baselines, and neural gradient flo...
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