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Irreversible Monte Carlo Algorithms for Hard Disk Glasses: From Event-Chain to Collective Swaps
Federico Ghimenti1, Ludovic Berthier2,3, Frédéric van Wijland1
1<a href="https://ror.org/032w6q449">Laboratoire Matière et Systèmes Complexes (MSC)</a>, Université Paris Cité & CNRS (UMR 7057), 75013 Paris, France.
Abstract:
Equilibrium sampling of the configuration space in disordered systems requires algorithms that bypass the glassy slowing down of the physical dynamics. Irreversible Monte Carlo algorithms breaking detailed balance successfully accelerate sampling in some systems. We first implement an irreversible event-chain Monte Carlo algorithm in a model of continuously polydisperse hard disks. The effect of collective translational moves marginally affects the dynamics and results in a modest speedup that decreases with density. We then propose an irreversible algorithm performing collective particle swaps which outperforms all known Monte Carlo algorithms. We show that these collective swaps can also be used to prepare very dense jammed packings of disks.
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