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Bypassing sluggishness: SWAP algorithm and glassiness in high dimensions

Ludovic Berthier, Patrick Charbonneau, and Joyjit Kundu
Phys. Rev. E 99, 031301(R) – Published 4 March 2019
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Abstract

The recent implementation of a swap Monte Carlo algorithm (SWAP) for polydisperse glass forming mixtures bypasses computational sluggishness and closes the gap between experimental and simulation timescales in physical dimensions d=2 and 3. Here, we consider suitably optimized systems in d=2,3,,8 to obtain insights into the performance and underlying physics of SWAP. We show that the speedup obtained decays rapidly with increasing the dimension. SWAP nonetheless delays systematically the onset of the activated dynamics by an amount that remains seemingly finite in the limit d. This shows that the glassy dynamics in high dimensions d>3 is now computationally accessible using SWAP, thus opening the door for the systematic consideration of finite-dimensional deviations from the mean-field description.

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  • Received 15 October 2018

DOI:https://doi.org/10.1103/PhysRevE.99.031301

©2019 American Physical Society

Physics Subject Headings (PhySH)

Statistical Physics & Thermodynamics

Authors & Affiliations

Ludovic Berthier1, Patrick Charbonneau2,3, and Joyjit Kundu2,*

  • 1Laboratoire Charles Coulomb (L2C), University of Montpellier, CNRS, Montpellier, France
  • 2Department of Chemistry, Duke University, Durham, North Carolina 27708, USA
  • 3Department of Physics, Duke University, Durham, North Carolina 27708, USA

  • *joyjitkundu032@gmail.com

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Issue

Vol. 99, Iss. 3 — March 2019

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