Quantifying Memory in Spin Glasses Article Swipe

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supercomputer spin glass computer science spin (aerodynamics) statistical physics spin offs materials science physics parallel computing condensed matter physics thermodynamics business industrial organization

I. Paga , J. P. He , Marco Baity‐Jesi , Enrico Calore , A. Cruz , L. A. Fernández , J. M. Gil-Narvion , I. González-Adalid Pemartín , A. Gordillo-Guerrero , D. Íñiguez , A. Maiorano , Enzo Marinari , V. Martı́n-Mayor , J. Moreno-Gordo , A. Muñoz Sudupe , D. Navarro , R. Orbach , Giorgio Parisi , S. Pérez-Gaviro , Federico Ricci‐Tersenghi , J. J. Ruiz-Lorenzo , Sebastiano Fabio Schifano , D. L. Schlagel , Beatriz Seoane , A. Tarancón , David Yllanes ·

YOU? · · 2024 · Open Access · · DOI: https://doi.org/10.1103/physrevlett.133.256704 · OA: W4405669234

Rejuvenation and memory, long considered the distinguishing features of spin glasses, have recently been proven to result from the growth of multiple length scales. This insight, enabled by simulations on the Janus II supercomputer, has opened the door to a quantitative analysis. We combine numerical simulations with comparable experiments to introduce two coefficients that quantify memory. A third coefficient has been recently presented by Freedberg et al. We show that these coefficients are physically equivalent by studying their temperature and waiting-time dependence.