Analysis of autocorrelation times in Neural Markov Chain Monte Carlo simulations. (arXiv:2111.10189v2 [cond-mat.stat-mech] UPDATED)

We provide a deepened study of autocorrelations in Neural Markov Chain Monte
Carlo simulations, a version of the traditional Metropolis algorithm which
employs neural networks to provide independent proposals. We illustrate our
ideas using the two-dimensional Ising model. We propose several estimates of
autocorrelation times, some inspired by analytical results derived for the
Metropolized Independent Sampler, which we compare and study as a function of
inverse temperature $\beta$. Based on that we propose an alternative loss
function and study its …

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