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Determinations of structure functions and parton distribution functions have been recently obtained using Monte Carlo methods and neural networks as universal, unbiased interpolants for the unknown functional dependence. In this work the…

High Energy Physics - Phenomenology · Physics 2009-11-18 Luigi Del Debbio , Alberto Guffanti , Andrea Piccione

The fractal structure of spin clusters and their boundaries in the critical two-dimensional (2D) Ising model is investigated numerically. The fractal dimensions of these geometrical objects are estimated by means of Monte Carlo simulations…

Statistical Mechanics · Physics 2009-11-10 Wolfhard Janke , Adriaan M. J. Schakel

A method is proposed for exactly calculating the partition function of a rectangular Ising lattice with the presence of a uniform external field. This approach is based on the method of the transfer matrix developed about seventy years ago…

General Physics · Physics 2013-10-02 C. B. Yang

Multiscale phenomena which include several processes occuring simultaneously at different length scales and exchanging energy with each other, are widespread in magnetism. These phenomena often govern the magnetization reversal dynamics,…

Materials Science · Physics 2009-10-31 V. V. Dobrovitski , M. I. Katsnelson , B. N. Harmon

We employ a procedure that enables us to calculate the excess free energies for a finite Ising cylinder with domain walls analytically. This procedure transparently covers all possible configurations of the domain walls under given boundary…

Statistical Mechanics · Physics 2025-06-23 Alessio Squarcini , Piotr Nowakowski , Douglas B. Abraham , Anna Maciołek

The dynamical hysteresis is studied in the kinetic Ising model in the presence of a sinusoidal magnetic field both by Monte Carlo simulation and by solving the dynamical meanfield equation for the averaged magnetisation. The frequency…

Condensed Matter · Physics 2007-05-23 Muktish Acharyya

The class of two-spin systems contains several important models, including random independent sets and the Ising model of statistical physics. We show that for both the hard-core (independent set) model and the anti-ferromagnetic Ising…

Probability · Mathematics 2012-03-13 Allan Sly , Nike Sun

We use an efficient method that eases the daunting task of simulating dynamics in spin systems with long-range interaction. Our Monte Carlo simulations of the long-range Ising model for the nonequilibrium phase ordering dynamics in two…

Statistical Mechanics · Physics 2019-01-23 Henrik Christiansen , Suman Majumder , Wolfhard Janke

Acceptance-rejection (AR), Independent Metropolis Hastings (IMH) or importance sampling (IS) Monte Carlo (MC) simulation algorithms all involve computing ratios of probability density functions (pdfs). On the other hand, classifiers…

Methodology · Statistics 2023-09-11 Elouan Argouarc'h , François Desbouvries

The form factor bootstrap approach is used to compute the exact contributions in the large distance expansion of the correlation function $<\sigma(x) \sigma(0)>$ of the two-dimensional Ising model in a magnetic field at $T=T_c$. The matrix…

High Energy Physics - Theory · Physics 2009-10-28 G. Delfino , G. Mussardo

We consider MAP estimators for structured prediction with exponential family models. In particular, we concentrate on the case that efficient algorithms for uniform sampling from the output space exist. We show that under this assumption…

Machine Learning · Computer Science 2012-05-14 Shankar Vembu , Thomas Gartner , Mario Boley

We present a new Monte Carlo method to calculate Casimir forces acting on objects in a near-critical fluid, considering the two basic cases of a wall and a sphere embedded in a two-dimensional Ising medium. During the simulation, the…

Statistical Mechanics · Physics 2014-06-19 Hendrik Hobrecht , Alfred Hucht

We study the ionic distribution near a charged surface. A new method for performing Monte Carlo simulations in this geometry is discussed. A theory is then presented that allows us to accurately reproduce the density profiles obtained in…

Chemical Physics · Physics 2012-11-09 Alexandre P. dos Santos , Yan Levin

In this paper we relate the partition function to the max-statistics of random variables. In particular, we provide a novel framework for approximating and bounding the partition function using MAP inference on randomly perturbed models. As…

Machine Learning · Computer Science 2012-07-03 Tamir Hazan , Tommi Jaakkola

The shell model Monte Carlo (SMMC) method is a powerful method for calculating exactly (up to statistical errors) thermal observables and statistical properties of atomic nuclei. However, its application has been limited by a sign problem…

Nuclear Theory · Physics 2025-01-08 Y. Alhassid , P. Fanto , C. Özen

We study the three-dimensional Ising model at the critical point in the fixed-magnetization ensemble, by means of the recently developed geometric cluster Monte Carlo algorithm. We define a magnetic-field-like quantity in terms of…

Statistical Mechanics · Physics 2009-10-31 H. W. J. Blöte , J. R. Heringa , M. M. Tsypin

We represent a general procedure for calculating the partition function of an Ising model on a one dimensional Fibonacci lattice in presence of magnetic field.This partition function can be written as a sum of partition functions of usual…

Statistical Mechanics · Physics 2007-05-23 Susanta Bhattacharya , Samir K. Paul

Exact expressions of the boundary state and the form factors of the Ising model are used to derive differential equations for the one-point functions of the energy and magnetization operators of the model in the presence of a boundary…

High Energy Physics - Theory · Physics 2009-10-28 R. Konik , A. LeClair , G. Mussardo

We study the problem of approximating the partition function of the ferromagnetic Ising model in graphs and hypergraphs. Our first result is a deterministic approximation scheme (an FPTAS) for the partition function in bounded degree graphs…

Data Structures and Algorithms · Computer Science 2018-12-26 Jingcheng Liu , Alistair Sinclair , Piyush Srivastava

Graphical models represent multivariate and generally not normalized probability distributions. Computing the normalization factor, called the partition function, is the main inference challenge relevant to multiple statistical and…

Machine Learning · Computer Science 2020-09-01 Michael Chertkov , Vladimir Chernyak , Yury Maximov