Data and scripts from: Bypassing sluggishness: SWAP algorithm and glassiness in high dimensions

Public

  • The recent implementation of a swap Monte Carlo algorithm (SWAP) for polydisperse mixtures fully 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 finite in the limit d -> infinity. 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. ... [Read More]

Total Size
289 files (1.62 MB)
Data Citation
  • Berthier, L., Charbonneau, P., Kundu, J. (2019). Data and scripts from: Bypassing sluggishness: SWAP algorithm and glassiness in high dimensions. Duke Digital Repository. https://doi.org/10.7924/r49w0dr6j
DOI
  • 10.7924/r49w0dr6j
Publication Date
ARK
  • ark:/87924/r49w0dr6j
Type
Format
Related Materials
Funding Agency
  • Simons Foundation
Grant Number
  • #454933
  • #454937
Contact
Title
  • Data and scripts from: Bypassing sluggishness: SWAP algorithm and glassiness in high dimensions

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