• Open Access

Breakdown of Ergodicity and Self-Averaging in Polar Flocks with Quenched Disorder

Yu Duan, Benoît Mahault, Yu-qiang Ma, Xia-qing Shi, and Hugues Chaté
Phys. Rev. Lett. 126, 178001 – Published 28 April 2021
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Abstract

We show that spatial quenched disorder affects polar active matter in ways more complex and far reaching than heretofore believed. Using simulations of the 2D Vicsek model subjected to random couplings or a disordered scattering field, we find in particular that ergodicity is lost in the ordered phase, the nature of which we show to depend qualitatively on the type of quenched disorder: for random couplings, it remains long-range ordered, but qualitatively different from the pure (disorderless) case. For random scatterers, polar order varies with system size but we find strong non-self-averaging, with sample-to-sample fluctuations dominating asymptotically, which prevents us from elucidating the asymptotic status of order.

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  • Received 6 October 2020
  • Revised 10 January 2021
  • Accepted 26 February 2021

DOI:https://doi.org/10.1103/PhysRevLett.126.178001

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)

Polymers & Soft Matter

Authors & Affiliations

Yu Duan1, Benoît Mahault2, Yu-qiang Ma1, Xia-qing Shi3, and Hugues Chaté4,5

  • 1National Laboratory of Solid State Microstructures and Department of Physics, Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing 210093, China
  • 2Max Planck Institute for Dynamics and Self-Organization (MPIDS), 37077 Göttingen, Germany
  • 3Center for Soft Condensed Matter Physics and Interdisciplinary Research, Soochow University, Suzhou 215006, China
  • 4Service de Physique de l’Etat Condensé, CEA, CNRS, Université Paris-Saclay, CEA-Saclay, 91191 Gif-sur-Yvette, France
  • 5Computational Science Research Center, Beijing 100193, China

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Issue

Vol. 126, Iss. 17 — 30 April 2021

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