Bypassing sluggishness: SWAP algorithm and glassiness in high dimensions

Berthier, Ludovic

Charbonneau, Patrick

Kundu, Joyjit

2019-02-05T01:55:43Z

2019-02-05T01:55:43Z

2019-02-05T01:55:42Z

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.

https://hdl.handle.net/10161/18059

American Physical Society (APS)

cond-mat.stat-mech

cond-mat.stat-mech

cond-mat.dis-nn

cond-mat.soft

Bypassing sluggishness: SWAP algorithm and glassiness in high dimensions

Journal article

Charbonneau, Patrick|0000-0001-7174-0821

Trinity College of Arts & Sciences

Duke

Chemistry

Physics