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# Bypassing sluggishness: SWAP algorithm and glassiness in high dimensions

 dc.contributor.author Charbonneau, Patrick dc.contributor.author Berthier, Ludovic dc.contributor.author Kundu, Joyjit dc.date.accessioned 2019-02-05T01:55:43Z dc.date.available 2019-02-05T01:55:43Z dc.identifier.uri https://hdl.handle.net/10161/18059 dc.description.abstract 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 $d=2, 3,\dots, 8$, 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 $d \to \infty$. 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. dc.subject cond-mat.stat-mech dc.subject cond-mat.stat-mech dc.subject cond-mat.dis-nn dc.subject cond-mat.soft dc.title Bypassing sluggishness: SWAP algorithm and glassiness in high dimensions dc.type Journal article dc.date.updated 2019-02-05T01:55:42Z pubs.organisational-group Trinity College of Arts & Sciences pubs.organisational-group Duke pubs.organisational-group Chemistry pubs.organisational-group Physics duke.contributor.orcid Charbonneau, Patrick|0000-0001-7174-0821
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