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Unitary Long-Time Evolution with Quantum Renormalization Groups and Artificial Neural Networks

Heiko Burau and Markus Heyl
Phys. Rev. Lett. 127, 050601 – Published 27 July 2021
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Abstract

In this work, we combine quantum renormalization group approaches with deep artificial neural networks for the description of the real-time evolution in strongly disordered quantum matter. We find that this allows us to accurately compute the long-time coherent dynamics of large many-body localized systems in nonperturbative regimes including the effects of many-body resonances. Concretely, we use this approach to describe the spatiotemporal buildup of many-body localized spin-glass order in random Ising chains. We observe a fundamental difference to a noninteracting Anderson insulating Ising chain, where the order only develops over a finite spatial range. We further apply the approach to strongly disordered two-dimensional Ising models, highlighting that our method can be used also for the description of the real-time dynamics of nonergodic quantum matter in a general context.

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  • Received 1 October 2020
  • Revised 12 April 2021
  • Accepted 10 June 2021

DOI:https://doi.org/10.1103/PhysRevLett.127.050601

Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI. Open access publication funded by the Max Planck Society.

Published by the American Physical Society

Physics Subject Headings (PhySH)

Quantum Information, Science & TechnologyNonlinear DynamicsCondensed Matter, Materials & Applied Physics

Authors & Affiliations

Heiko Burau* and Markus Heyl

  • Max-Planck-Institut für Physik Komplexer Systeme, Nöthnitzer Straße 38, 01187 Dresden, Germany

  • *burau@pks.mpg.de

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Issue

Vol. 127, Iss. 5 — 30 July 2021

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