Regensburg 2022 – wissenschaftliches Programm
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O: Fachverband Oberflächenphysik
O 67: Frontiers of Electronic Structure Theory: Focus on Artificial Intelligence Applied to Real Materials 3
O 67.9: Vortrag
Donnerstag, 8. September 2022, 12:30–12:45, S054
Machine Learning the Square-Lattice Ising Model — •Burak Çivitcioğlu1, Andreas Honecker1, and Rudolf A. Römer2 — 1Laboratoire de Physique Theorique et Modelisation, CNRS UMR 8089, CY Cergy Paris Universit *e, Cergy-Pontoise, France — 2Department of Physics, University of Warwick, Coventry, CV4 7AL, United Kingdom
Recently, machine-learning methods have been shown to be successful in identifying and classifying different phases of the square-lattice Ising model. We study the performance and limits of classification and regression models. In particular, we investigate how accurately the correlation length, energy and magnetisation can be recovered from a given configuration. We find that a supervised learning study of a regression model yields good predictions for magnetisation and energy, and acceptable predictions for the correlation length.