TY - JOUR
T1 - The three-dimensional Ising spin glass in an external magnetic field
T2 - The role of the silent majority
AU - Baity-Jesi, M.
AU - Baños, R. A.
AU - Cruz, A.
AU - Fernandez, L. A.
AU - Gil-Narvion, J. M.
AU - Gordillo-Guerrero, A.
AU - Iñiguez, D.
AU - Maiorano, A.
AU - Mantovani, F.
AU - Marinari, E.
AU - Martin-Mayor, V.
AU - Monforte-Garcia, J.
AU - Muñoz Sudupe, A.
AU - Navarro, D.
AU - Parisi, G.
AU - Perez-Gaviro, S.
AU - Pivanti, M.
AU - Ricci-Tersenghi, F.
AU - Ruiz-Lorenzo, J. J.
AU - Schifano, S. F.
AU - Seoane, B.
AU - Tarancon, A.
AU - Tripiccione, R.
AU - Yllanes, D.
PY - 2014/5
Y1 - 2014/5
N2 - We perform equilibrium parallel-tempering simulations of the 3D Ising Edwards-Anderson spin glass in a field, using the Janus computer. A traditional analysis shows no signs of a phase transition. However, we encounter dramatic fluctuations in the behaviour of the model: averages over all the data only describe the behaviour of a small fraction of the data. Therefore, we develop a new approach to study the equilibrium behaviour of the system, by classifying the measurements as a function of a conditioning variate. We propose a finite-size scaling analysis based on the probability distribution function of the conditioning variate, which may accelerate the convergence to the thermodynamic limit. In this way, we find a non-trivial spectrum of behaviours, where some of the measurements behave as the average, while the majority show signs of scale invariance. As a result, we can estimate the temperature interval where the phase transition in a field ought to lie, if it exists. Although this would-be critical regime is unreachable with present resources, the numerical challenge is finally well posed.
AB - We perform equilibrium parallel-tempering simulations of the 3D Ising Edwards-Anderson spin glass in a field, using the Janus computer. A traditional analysis shows no signs of a phase transition. However, we encounter dramatic fluctuations in the behaviour of the model: averages over all the data only describe the behaviour of a small fraction of the data. Therefore, we develop a new approach to study the equilibrium behaviour of the system, by classifying the measurements as a function of a conditioning variate. We propose a finite-size scaling analysis based on the probability distribution function of the conditioning variate, which may accelerate the convergence to the thermodynamic limit. In this way, we find a non-trivial spectrum of behaviours, where some of the measurements behave as the average, while the majority show signs of scale invariance. As a result, we can estimate the temperature interval where the phase transition in a field ought to lie, if it exists. Although this would-be critical regime is unreachable with present resources, the numerical challenge is finally well posed.
UR - https://www.scopus.com/pages/publications/84902282301
U2 - 10.1088/1742-5468/2014/05/P05014
DO - 10.1088/1742-5468/2014/05/P05014
M3 - 文章
AN - SCOPUS:84902282301
SN - 1742-5468
VL - 2014
JO - Journal of Statistical Mechanics: Theory and Experiment
JF - Journal of Statistical Mechanics: Theory and Experiment
IS - 5
M1 - P05014
ER -