English
Related papers

Related papers: Configurational Mean-Field Reduced Transfer Matrix…

200 papers

Mean-field theory is an approximation replacing an extended system by a few variables. For depinning of elastic manifolds, these are the position of its center of mass $u$, and the statistics of the forces $F(u)$. There are two proposals to…

Statistical Mechanics · Physics 2022-01-19 Cathelijne ter Burg , Kay Joerg Wiese

We present an alternative procedure for solving the eigenvalue problem of replicated transfer matrices describing disordered spin systems with (random) 1D nearest neighbor bonds and/or random fields, possibly in combination with (random)…

Disordered Systems and Neural Networks · Physics 2009-11-10 T. Nikoletopoulos , A. C. C. Coolen

The principle and the efficiency of the Monte Carlo transfer-matrix algorithm are discussed. Enhancements of this algorithm are illustrated by applications to several phase transitions in lattice spin models. We demonstrate how the…

Condensed Matter · Physics 2009-10-28 M. P. Nightingale , H. W. J. Bloete

We compare dynamic mean-field and dynamic cavity as methods to describe the stationary states of dilute kinetic Ising models. We compute dynamic mean-field theory by expanding in interaction strength to third order, and compare to the exact…

Disordered Systems and Neural Networks · Physics 2012-03-21 Erik Aurell , Hamed Mahmoudi

An entropy of the Ising model in the mean field approximation is derived by the Hamilton-Jacobi formalism. We consider a grand canonical ensemble with respect to the temperature and the external magnetic field. A cusp arises at the critical…

Mathematical Physics · Physics 2017-10-25 Yayoi Abe , Muneyuki Ishida , Erika Nozawa , Takayoshi Ootsuka , Ryoko Yahagi

Dynamical mean-field theory (DMFT) is a cornerstone technique for studying strongly correlated electronic systems. However, each DMFT step is computationally demanding, and many iterations can be required to achieve convergence. Here, we…

Strongly Correlated Electrons · Physics 2026-01-26 E. M. Makaresz , O. Gingras , Tsung-Han Lee , Nicola Lanatà , B. J. Powell , Henry L. Nourse

Equilibrium properties of long-range interacting systems on lattices are investigated. There was a conjecture by Cannas et. al. that the mean-field theory is exact for spin systems with non-additive long-range interactions. This is called…

Statistical Mechanics · Physics 2011-10-31 Takashi Mori

We introduce $S_z$ spin-projection based on cluster mean-field theory and apply it to the ground state of strongly-correlated spin systems. In cluster mean-field, the ground state wavefunction is written as a factorized tensor product of…

Strongly Correlated Electrons · Physics 2023-08-24 Athanasios Papastathopoulos-Katsaros , Thomas M. Henderson , Gustavo E. Scuseria

Mean-field stochastic differential equations, also called McKean--Vlasov equations, are the limiting equations of interacting particle systems with fully symmetric interaction potential. Such systems play an important role in a variety of…

Dynamical Systems · Mathematics 2025-09-15 Eirini Ioannou , Stefan Klus , Gonçalo dos Reis

Despite their formal simplicity, most lattice spin models cannot be easily solved, even under the simplifying assumptions of mean field theory. In this manuscript, we present a method for generating mean field solutions to classical…

Statistical Mechanics · Physics 2022-06-22 Yizhi Shen , Adam P. Willard

In this paper, we present an innovative particle system characterized by moderate interactions, designed to accurately approximate kinetic flocking models that incorporate singular interaction forces and local alignment mechanisms. We…

Analysis of PDEs · Mathematics 2024-04-23 Jinhuan Wang , Keyu Li , Hui Huang

A pathwise large deviation principle in the Wasserstein topology and a pathwise central limit theorem are proved for the empirical measure of a mean-field system of interacting diffusions. The coefficients are path-dependent. The framework…

Probability · Mathematics 2024-10-10 Louis-Pierre Chaintron

Using the technique of mean field theory applied to the lattice boundary Ising and tricritical Ising models we provide a qualitative description of their boundary phase diagrams. We will show this is in agreement with the known picture from…

Statistical Mechanics · Physics 2011-06-10 Philip Giokas

We consider an application of probabilistic coupling techniques which provides explicit estimates for comparison of local expectation values between label permutation invariant states, for instance, between certain microcanonical,…

Mathematical Physics · Physics 2020-08-26 Kalle Koskinen , Jani Lukkarinen

Recently a local mean field theory for both eqilibrium and transport properties of the Coulomb glass was proposed [A. Amir et al., Phys. Rev. B 77, 165207 (2008); 80, 245214 (2009)]. We compare the predictions of this theory to the results…

Disordered Systems and Neural Networks · Physics 2012-12-03 E. Bardalen , J. Bergli , Y. M. Galperin

A mean field feedback artificial neural network algorithm is developed and explored for the set covering problem. A convenient encoding of the inequality constraints is achieved by means of a multilinear penalty function. An approximate…

Neural and Evolutionary Computing · Computer Science 2007-05-23 Mattias Ohlsson , Carsten Peterson , Bo Söderberg

The possibility to apply phase-space methods to many-body interacting systems might provide accurate descriptions of correlations with a reduced numerical cost. For instance, the so--called stochastic mean-field phase-space approach, where…

Nuclear Theory · Physics 2020-04-22 Thomas Czuba , Denis Lacroix , David Regnier , Ibrahim Ulgen , Bulent Yilmaz

The extended dynamical mean field theory has played an important role in the study of quantum phase transitions in heavy fermion systems. In order to incorporate the physics of unconventional superconductivity, we develop a cluster version…

Strongly Correlated Electrons · Physics 2015-05-19 J. H. Pixley , Ang Cai , Qimiao Si

Many real-world phenomena can be modelled as dynamical processes on networks, a prominent example being the spread of infectious diseases such as COVID-19. Mean-field approximations are a widely used tool to analyse such dynamical processes…

Probability · Mathematics 2025-08-25 Jonathan A. Ward , Gábor Timár , Péter L. Simon

We consider the Hamiltonians of mean-field spin glasses, which are certain random functions $H_N$ defined on high-dimensional cubes or spheres in $\mathbb R^N$. The asymptotic maximum values of these functions were famously obtained by…

Disordered Systems and Neural Networks · Physics 2024-01-23 Mark Sellke