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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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