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We investigate the non-equilibrium dynamics of isolated quantum spin systems via an exact mapping to classical stochastic differential equations. We show that one can address significantly larger system sizes than recently obtained,…

Strongly Correlated Electrons · Physics 2020-12-30 S. E. Begg , A. G. Green , M. J. Bhaseen

A sampling method for spin systems is presented. The spin lattice is written as the union of a nested sequence of sublattices, all but the last with conditionally independent spins, which are sampled in succession using their marginals. The…

Numerical Analysis · Mathematics 2008-02-09 Alexandre Chorin

Similarities between fragile glasses and spin glasses (SG) suggest the study of frustrated spin model to understand the complex dynamics of glasses above the glass transition. We consider a frustrated spin model with Ising spins and s-state…

Disordered Systems and Neural Networks · Physics 2007-05-23 Giancarlo Franzese , Antonio Coniglio

Spin-glass and chiral-glass orderings of a three-dimensional isotropic Heisenberg spin glass are studied both by equilibrium and off-equilibrium Monte Carlo simulations with emphasis on their dynamical aspects. The model is found to exhibit…

Disordered Systems and Neural Networks · Physics 2007-05-23 H. Kawamura , K. Hukushima

A powerful existing technique for evaluating statistical mechanical quantities in two-dimensional Ising models is based on constructing a matrix representing the nearest neighbor spin couplings and then evaluating the Pfaffian of the…

Disordered Systems and Neural Networks · Physics 2013-04-16 Creighton K. Thomas , A. Alan Middleton

We perform Monte Carlo simulations of Ising spin-glass models in three and four dimensions, as well as of Migdal-Kadanoff spin glasses on a hierarchical lattice. Our results show strong evidence for universal scaling in the spin-glass phase…

Disordered Systems and Neural Networks · Physics 2008-11-05 Thomas Jorg , Helmut G. Katzgraber

Monte Carlo data of the two-dimensional Ising spin glass with bimodal interactions are presented with the aim of understanding the low-temperature physics of the model. An analysis of the specific heat, spin-glass susceptibility,…

Disordered Systems and Neural Networks · Physics 2007-05-23 Helmut G. Katzgraber , Lik Wee Lee , I. A. Campbell

In dynamic Monte Carlo simulations, using for example the Metropolis dynamic, it is often required to simulate for long times and to simulate large systems. We present an overview of advanced algorithms to simulate for larger times and to…

Statistical Mechanics · Physics 2007-05-23 M. A. Novotny , Alice K. Kolakowska , G. Korniss

In a recent letter [Phys. Rev. Lett. {\bf 100}, 164101 (2008)] and within the context of quantized chaotic billiards, random plane wave and semiclassical theoretical approaches were applied to an example of a relatively new class of…

Mesoscale and Nanoscale Physics · Physics 2013-05-29 Denis Ullmo , Steven Tomsovic , Arnd Baecker

We perform high-statistics Monte Carlo simulations of three-dimensional Ising spin-glass models on cubic lattices of size L: the +- J (Edwards-Anderson) Ising model for two values of the disorder parameter p, p=0.5 and p=0.7 (up to L=28 and…

Disordered Systems and Neural Networks · Physics 2009-11-13 Martin Hasenbusch , Andrea Pelissetto , Ettore Vicari

We consider the problem of predicting the spin states in a kinetic Ising model when spin trajectories are observed for only a finite fraction of sites. In a Bayesian setting, where the probabilistic model of the spin dynamics is assumed to…

Disordered Systems and Neural Networks · Physics 2015-06-19 Ludovica Bachschmid Romano , Manfred Opper

Numerical simulations of models and theories that describe complex systems such as spin glasses are becoming increasingly important. Beyond fundamental research, these computational methods also find practical applications in fields like…

Spin glass systems as lattices of disordered magnets with random interactions have important implications within the theory of magnetization and applications to a wide-range of hard combinatorial optimization problems. Nevertheless, despite…

Disordered Systems and Neural Networks · Physics 2025-10-28 Fredrik Hasselgren , Max O. Al-Hasso , Amy Searle , Joseph Tindall , Marko von der Leyen

Monte Carlo simulations are based on the manipulation of random numbers to evaluate probable outcomes, with applicability in a variety of different fields. By assigning probabilities, which can be determined a priori, to various events, it…

Physics Education · Physics 2022-01-03 Parasuraman Swaminathan

We investigate the impact of internal spin on chaos in billiard systems. Extending the standard point-particle billiard by coupling translational and rotational degrees of freedom through a dimensionless spin parameter $\alpha = I/(mr^2)…

Chaotic Dynamics · Physics 2026-03-31 Jacob S. Lund , Jeff Murugan , Jonathan P. Shock

In the finite-size scaling analysis of Monte Carlo data, instead of computing the observables at fixed Hamiltonian parameters, one may choose to keep a renormalization-group invariant quantity, also called phenomenological coupling, fixed…

Statistical Mechanics · Physics 2011-08-31 Francesco Parisen Toldin

Many popular statistical models for complex phenomena are intractable, in the sense that the likelihood function cannot easily be evaluated. Bayesian estimation in this setting remains challenging, with a lack of computational methodology…

Computation · Statistics 2015-03-31 Nial Friel , Antonietta Mira , Chris. J. Oates

The construction of a statistical model for eigenfunctions of the Ising model in transverse and longitudinal fields is discussed in detail for the chaotic case. When the number of spins is large, each wave function coefficient has the…

Mathematical Physics · Physics 2015-03-17 Y. Y. Atas , E. Bogomolny

We perform numerical simulations to study static and dynamic critical behaviour of the 3d random-site Ising model. A distinct feature of our approach is a combination of the Metropolis, Swendsen-Wang, and Wolff Monte Carlo algorithms. For…

Disordered Systems and Neural Networks · Physics 2009-04-03 D. Ivaneyko , J. Ilnytskyi , B. Berche , Yu. Holovatch

A driven Monte Carlo dynamics is introduced to study resistivity scaling in XY-type models in the phase representation. The method is used to study the phase transition of the three-dimensional XY spin glass with a Gaussian coupling…

Disordered Systems and Neural Networks · Physics 2009-11-10 Enzo Granato