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Solving Statistical Mechanics on Sparse Graphs with Feedback Set Variational Autoregressive Networks
[article]
2020
arXiv
pre-print
We propose a method for solving statistical mechanics problems defined on sparse graphs. It extracts a small Feedback Vertex Set (FVS) from the sparse graph, converting the sparse system to a much smaller system with many-body and dense interactions with an effective energy on every configuration of the FVS, then learns a variational distribution parameterized using neural networks to approximate the original Boltzmann distribution. The method is able to estimate free energy, compute
arXiv:1906.10935v2
fatcat:zt3notnp7fewtitf2pq2bat4oa