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We propose a general quantitative scheme in which systems are given the freedom to sacrifice energy equi-partitioning on the relevant time-scales of observation, and have phase transitions by separating autonomously into ergodic sub-systems…

Statistical Mechanics · Physics 2009-10-31 A. C. C. Coolen , J. van Mourik

We sketch a new framework for the analysis of disordered systems, in particular mean field spin glasses, which is variational in nature and within the formalism of classical thermodynamics. For concreteness, only the Sherrington-Kirkpatrick…

Probability · Mathematics 2019-02-26 Goetz Kersting , Nicola Kistler , Adrien Schertzer , Marius A. Schmidt

We study hierarchies of replica-symmetry-breaking solutions of the Sherrington-Kirkpatrick model. Stationarity equations for order parameters of solutions with an arbitrary number of hierarchies are set and the limit to infinite number of…

Disordered Systems and Neural Networks · Physics 2008-09-16 V Janis , A. Klic , M. Ringel

The Parisi formula for the free energy of the Sherrington-Kirkpatrick model is completed to a closed-form generating functional. We first find an integral representation for a solution of the Parisi differential equation and represent the…

Disordered Systems and Neural Networks · Physics 2008-09-16 V. Janis

We consider the problems of chaos in disorder and temperature for coupled copies of the mixed p-spin models. Under certain assumptions on the parameters of the models we will first prove a weak form of chaos by showing that the overlap is…

Probability · Mathematics 2013-09-18 Wei-Kuo Chen , Dmitry Panchenko

We show that the limiting ground state energy of the spherical mixed p-spin model can be identified as the infimum of certain variational problem. This complements the well-known Parisi formula for the limiting free energy in the spherical…

Probability · Mathematics 2017-01-04 Wei-Kuo Chen , Arnab Sen

We consider a spin system obtained by coupling two distinct Sherrington-Kirkpatrick (SK) models with the same temperature and external field whose Hamiltonians are correlated. The disorder chaos conjecture for the SK model states that the…

Probability · Mathematics 2013-10-04 Wei-Kuo Chen

We use real replicas within the Thouless, Anderson and Palmer construction to investigate stability of solutions with respect to uniform scalings in the phase space of the Sherrington-Kirkpatrick model. We show that the demand of…

Disordered Systems and Neural Networks · Physics 2008-09-16 V. Janis

To describe the equilibrium properties of disordered systems and the possible emergence of various 'phases' at low temperature, we adopt here the 'broken ergodicity' point of view advocated in particular by Palmer [Adv. Phys. 31, 669…

Disordered Systems and Neural Networks · Physics 2008-08-18 Cecile Monthus , Thomas Garel

It was proved by Michel Talagrand in [10] that the Parisi formula for the free energy in the Sherrington-Kirkpatrick model is differentiable with respect to inverse temperature parameter. We present a simpler proof of this result by using…

Probability · Mathematics 2008-05-04 Dmitry Panchenko

A scaling theory of replica symmetry breaking (RSB) in the SK-model is presented in the framework of critical phenomena for the scaling regime of small inverse RSB-orders, small temperatures, small magnetic fields, and near opposite…

Disordered Systems and Neural Networks · Physics 2009-11-13 Reinhold Oppermann , Manuel J. Schmidt

In this note we summarize the connections between equilibrium and slow out of equilibrium dynamics in finite dimensional glasses, such as we understand them today. If we assume that a finite-dimensional system is stable with respect to a…

Disordered Systems and Neural Networks · Physics 2022-07-13 Silvio Franz , Jorge Kurchan

In this paper we study the equilibrium statistical mechanical as well as the dynamical properties of a Sherrington and Kirkpatrick model in a multi-bath setting introduced in [4]. We show that the free energy per particle in the…

Disordered Systems and Neural Networks · Physics 2019-09-04 Pierluigi Contucci , Jorge Kurchan , Emanuele Mingione

In this review article, we discuss connections between the physics of disordered systems, phase transitions in inference problems, and computational hardness. We introduce two models representing the behavior of glassy systems, the spiked…

Disordered Systems and Neural Networks · Physics 2022-12-07 David Gamarnik , Cristopher Moore , Lenka Zdeborová

Configurational entropy, or complexity, plays a critical role in characterizing disordered systems such as glasses, yet its measurement often requires significant computational resources. Recently, R\'enyi entropy, a one-parameter…

Disordered Systems and Neural Networks · Physics 2025-08-27 Nina Javerzat , Eric Bertin , Misaki Ozawa

We study the probability distribution function of the ground-state energies of the disordered one-dimensional Ising spin chain with power-law interactions using a combination of parallel tempering Monte Carlo and branch, cut, and price…

Disordered Systems and Neural Networks · Physics 2007-05-23 Helmut G. Katzgraber , Mathias Koerner , Frauke Liers , Michael Juenger , A. K. Hartmann

The validity of the Parisi formula in the Sherrington-Kirkpatrick model (SK) was initially proved by Talagrand [18]. The central argument therein relied on a very dedicated study of the coupled free energy via the two-dimensional…

Probability · Mathematics 2016-05-16 Wei-Kuo Chen

The Parisi scheme for equilibrium and the corresponding slow dynamics with multithermalization - same temperature common to all observables, different temperatures only possible at widely separated timescales -- imply one another.…

Statistical Mechanics · Physics 2022-09-23 Jorge Kurchan

In a previous work [A simplified Parisi Ansatz, Franchini, S., Commun. Theor. Phys., 73, 055601 (2021)] we introduced a simple method to compute the Random Overlap Structure of Aizenmann, Simm and Stars and the full RSB Parisi formula for…

Statistical Mechanics · Physics 2025-10-07 Simone Franchini

The problem of time-series clustering is considered in the case where each data-point is a sample generated by a piecewise stationary ergodic process. Stationary processes are perhaps the most general class of processes considered in…

Machine Learning · Statistics 2019-06-27 Azadeh Khaleghi , Daniil Ryabko
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