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Examples of renormalization group transformations for image sets

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arxiv 1807.10250 v1 pith:76YJ7OH3 submitted 2018-07-26 hep-lat cond-mat.stat-mech

Samuel Foreman , Joel Giedt , Yannick Meurice , Judah Unmuth-Yockey This is my paper · ORCID
classification hep-latcond-mat.stat-mech
keywords grouprenormalizationsetstensortransformationsalgorithmappliedapproximation
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Using the example of configurations generated with the worm algorithm for the two-dimensional Ising model, we propose renormalization group (RG) transformations, inspired by the tensor RG, that can be applied to sets of images. We relate criticality to the logarithmic divergence of the largest principal component. We discuss the changes in link occupation under the RG transformation, suggest ways to obtain data collapse, and compare with the two state tensor RG approximation near the fixed point.

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