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Related papers: Sequential Dynamics in Ising Spin Glasses

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This lecture deals with glassy dynamics and aging in disordered systems. Special emphasis is put on dynamic mean field theory. In the first part I present some of the systems of interest, in particular spin-glasses, supercooled liquids and…

Disordered Systems and Neural Networks · Physics 2007-05-23 Heinz Horner

We discuss analytical approximation schemes for the dynamics of diluted spin models. The original dynamics of the complete set of degrees of freedom is replaced by a hierarchy of equations including an increasing number of global…

Statistical Mechanics · Physics 2009-11-10 Guilhem Semerjian , Martin Weigt

We study a fermionic version of the Sherrington-Kirkpatrick model including nearest-neighbor hopping on a $\infty$-dimensional simple cubic lattices. The problem is reduced to one of free fermions moving in a dynamical effective random…

Disordered Systems and Neural Networks · Physics 2009-11-10 M. Bechmann , R. Oppermann

In this note we present an exact solution of the Monte Carlo dynamics of the spherical Sherrington-Kirkpatrick spin-glass model. We obtain the dynamical equations for a generalized set of moments which can be exactly closed. Only in a…

Condensed Matter · Physics 2009-10-28 L. L. Bonilla , F. G. Padilla , G. Parisi , F. Ritort

Different sets of metastable states can be reached in glassy systems below some transition temperature depending on initial conditions and details of the dynamics. This is investigated for the Sherrington-Kirkpatrick spin glass model with…

Disordered Systems and Neural Networks · Physics 2015-03-13 Heinz Horner

We consider a version of a Glauber dynamics for a p-spin Sherrington--Kirkpatrick model of a spin glass that can be seen as a time change of simple random walk on the N-dimensional hypercube. We show that, for any p>2 and any inverse…

Probability · Mathematics 2007-07-17 Gerard Ben Arous , Anton Bovier , Jiri Cerny

We use a non-equilibrium simulation method to study the spin glass transition in three-dimensional Ising spin glasses. The transition point is repeatedly approached at finite velocity $v$ (temperature change versus time) in Monte Carlo…

Disordered Systems and Neural Networks · Physics 2015-08-26 C. -W. Liu , A. Polkovnikov , A. W. Sandvik , A. P. Young

A dimer mean-field model for the Ising spin-glass is presented. Despite its simplicity it captures some of the essential features of the spin-glass physics. The distribution of the single-spin magnetization is determined from a…

Disordered Systems and Neural Networks · Physics 2009-12-16 Yonatan Dubi , Massimiliano Di Ventra

We show by means of experiments, theory and simulations, that the slow dynamics of coarsening systems displays dynamic heterogeneity similar to that observed in glass-forming systems. We measure dynamic heterogeneity via novel multi-point…

We consider Glauber dynamics of classical spin systems of Ising type in the limit when the temperature tends to zero in finite volume. We show that information on the structure of the most profound minima and the connecting saddle points of…

Disordered Systems and Neural Networks · Physics 2015-06-24 Anton Bovier , Francesco Manzo

The short- and long-time dynamics of model systems undergoing a glass transition with apparent inversion of Kauzmann and dynamical arrest glass transition lines is investigated. These models belong to the class of the spherical mean-field…

Disordered Systems and Neural Networks · Physics 2016-01-06 Corrado Rainone , Ulisse Ferrari , Matteo Paoluzzi , Luca Leuzzi

We derive and study dynamical TAP equations for Ising spin glasses obeying both synchronous and asynchronous dynamics using a generating functional approach. The system can have an asymmetric coupling matrix, and the external fields can be…

Disordered Systems and Neural Networks · Physics 2011-05-17 Yasser Roudi , John Hertz

It is a folklore belief in the theory of spin glasses and disordered systems that out-of-equilibrium dynamics fail to find stable local optima exhibiting e.g. local strict convexity on physical time-scales. In the context of the…

Disordered Systems and Neural Networks · Physics 2026-04-02 Brice Huang , Mark Sellke

We consider zero-temperature, stochastic Ising models with nearest-neighbor interactions and an initial spin configuration chosen from a symmetric Bernoulli distribution (corresponding physically to a deep quench). Whether a final state…

Disordered Systems and Neural Networks · Physics 2009-10-31 C. M. Newman , D. L. Stein

Motivated by the recent development of quantum technology using quantum annealing technique and the recent works on the static properties of the Sherrington-Kirkpatrick (SK) spin glass model, we study quantum annealing of the spin glass…

Statistical Mechanics · Physics 2023-12-05 Atanu Rajak , Bikas K Chakrabarti

We investigate the inherent structure (IS) dynamics of mean-field {\it finite-size} spin-glass models whose high-temperature dynamics is described in the thermodynamic limit by the schematic Mode Coupling Theory for super-cooled liquids.…

Disordered Systems and Neural Networks · Physics 2009-10-31 A. Crisanti , F. Ritort

The dynamics of the spins in the Ising model are analyzed using a virtual walk scenario. The system is quenched from a very high temperature to a lower one using the Glauber scheme in one and two dimensions. A walk is associated with each…

Statistical Mechanics · Physics 2026-03-11 Amit Pradhan , Parongama Sen , Sagnik Seth

The complex dynamics of an increasing number of systems is attributed to the emergence of a rugged energy landscape with an exponential number of metastable states. To develop this picture into a predictive dynamical theory I discuss how to…

Disordered Systems and Neural Networks · Physics 2021-09-15 Tommaso Rizzo

Spin glasses, generally defined as disordered systems with randomized competing interactions, are a widely investigated complex system. Theoretical models describing spin glasses are broadly used in other complex systems, such as those…

We revisit the problem of efficiently learning the underlying parameters of Ising models from data. Current algorithmic approaches achieve essentially optimal sample complexity when given i.i.d. samples from the stationary measure and the…

Machine Learning · Computer Science 2023-11-16 Jason Gaitonde , Elchanan Mossel