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Title: Examples of renormalization group transformations for image sets

Abstract

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.

Authors:
; ; ;
Publication Date:
Research Org.:
Argonne National Lab. (ANL), Argonne, IL (United States)
Sponsoring Org.:
USDOE Office of Science - Office of High Energy Physics; USDOE Office of Science - Office of Workforce Development for Teachers and Scientists; USDOE Office of Science - Graduate Student Research (SCGSR) Program
OSTI Identifier:
1504259
DOE Contract Number:  
AC02-06CH11357
Resource Type:
Journal Article
Journal Name:
Physical Review E
Additional Journal Information:
Journal Volume: 98; Journal Issue: 5; Journal ID: ISSN 2470-0045
Publisher:
American Physical Society (APS)
Country of Publication:
United States
Language:
English

Citation Formats

Foreman, Samuel, Giedt, Joel, Meurice, Yannick, and Unmuth-Yockey, Judah. Examples of renormalization group transformations for image sets. United States: N. p., 2018. Web. doi:10.1103/PhysRevE.98.052129.
Foreman, Samuel, Giedt, Joel, Meurice, Yannick, & Unmuth-Yockey, Judah. Examples of renormalization group transformations for image sets. United States. doi:10.1103/PhysRevE.98.052129.
Foreman, Samuel, Giedt, Joel, Meurice, Yannick, and Unmuth-Yockey, Judah. Thu . "Examples of renormalization group transformations for image sets". United States. doi:10.1103/PhysRevE.98.052129.
@article{osti_1504259,
title = {Examples of renormalization group transformations for image sets},
author = {Foreman, Samuel and Giedt, Joel and Meurice, Yannick and Unmuth-Yockey, Judah},
abstractNote = {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.},
doi = {10.1103/PhysRevE.98.052129},
journal = {Physical Review E},
issn = {2470-0045},
number = 5,
volume = 98,
place = {United States},
year = {2018},
month = {11}
}