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Bypassing sluggishness: SWAP algorithm and glassiness in high dimensions.

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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… Click to show full 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.

Keywords: bypassing sluggishness; swap; swap algorithm; high dimensions; sluggishness swap

Journal Title: Physical review. E
Year Published: 2019

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