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Bulletin of the American Physical Society

Real-space renormalization group transformation from CNN and maximum likelihood estimation

Chak Ming Chan, Ding Wang, Tian Liang, Lei‐Han Tang

Published Mar 18, 2021• 0 citations
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The renormalization group (RG) methods are still far from being completely understood in quenched disordered systems. In order to gain insight into the nature of the phase transition of these systems, it is common to investigate simple models. In this work we study a real-space RG transformation on the Dyson hierarchical lattice with a random field, which leads to a reconstruction of the RG flow and to an evaluation of the critical exponents of the model at T=0. We show that this method gives very accurate estimations of the critical exponents by comparing our results with those obtained by some of us using an independent method.
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