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hep-lat2026
Exact and Near-Exact Inverse Renormalization Group with Constrained Monte Carlo
Dimitrios Bachtis
We establish conditions for exactness of the inverse renormalization group via constrained Markov processes, a class of Monte Carlo simulations which sample the degrees of freedom…
hep-lat2024
Generating configurations of increasing lattice size with machine learning and the inverse renormalization group
Dimitrios Bachtis
We review recent developments of machine learning algorithms pertinent to the inverse renormalization group, which was originally established as a generative numerical method by Ro…