Bypassing sluggishness: SWAP algorithm and glassiness in high dimensions Auteur(s): Berthier L., Charbonneau Patrick, Kundu Joyjit (Article) Publié: Physical Review E: Statistical, Nonlinear, And Soft Matter Physics, vol. p.031301 (2019) Texte intégral en Openaccess : Ref HAL: hal-02074910_v1 Ref Arxiv: 1810.06950 DOI: 10.1103/PhysRevE.99.031301 WoS: 000460663400001 Ref. & Cit.: NASA ADS Exporter : BibTex | endNote 8 Citations Résumé: 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. Commentaires: Réf Journal: Phys. Rev. E 99, 031301 (2019) |