An analysis of localization transitions using non-parametric unsupervised learning

• URL: http://arxiv.org/abs/2311.16050v2
• Date: Mon, 4 Mar 2024 14:51:04 GMT
• Title: An analysis of localization transitions using non-parametric unsupervised learning
• Authors: Carlo Vanoni, Vittorio Vitale
• Abstract summary: We show how critical properties can be seen as a geometric transition in the data space generated by the classically encoded configurations of the disordered quantum system. We estimate the transition point and critical exponents in agreement with the best-known results in the literature.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We propose a new viewpoint on the study of localization transitions in disordered quantum systems, showing how critical properties can be seen also as a geometric transition in the data space generated by the classically encoded configurations of the disordered quantum system. We showcase our approach to the Anderson model on regular random graphs, known for displaying features of interacting systems, despite being a single-particle problem. We estimate the transition point and critical exponents in agreement with the best-known results in the literature. We provide a simple and coherent explanation of our findings, discussing the applicability of the method in real-world scenarios with a modest number of measurements.

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