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Some results on the two-point function and on the analytic structure of the momenta of the effective fugacity at the origin for a class of diluted ferromagnetic Ising models on the Cayley tree are presented.

Statistical Mechanics · Physics 2016-08-31 J. C. A. Barata , D. H. U. Marchetti

We consider a family of quantum spin systems which includes as special cases the ferromagnetic XY model and ferromagnetic Ising model on any graph, with or without a transverse magnetic field. We prove that the partition function of any…

Quantum Physics · Physics 2017-09-13 Sergey Bravyi , David Gosset

In recent years, sequential importance sampling (SIS) has been well developed for sampling contingency tables with linear constraints. In this paper, we apply SIS procedure to 2-dimensional Ising models, which give observations of 0-1…

Computation · Statistics 2014-10-17 Jing Xi , Seth Sullivant

We apply extensive Monte Carlo simulations to study the probability distribution $P(m)$ of the order parameter $m$ for the simple cubic Ising model with periodic boundary condition at the transition point. Sampling is performed with the…

Computational Physics · Physics 2020-03-18 Jiahao Xu , Alan M. Ferrenberg , David P. Landau

The spin-1/2 Ising model on a square lattice, with fluctuating bond interactions between nearest neighbors and in the presence of a random magnetic field, is investigated within the framework of the effective field theory based on the use…

Statistical Mechanics · Physics 2013-04-10 Ioannis A. Hadjiagapiou

This paper proposes a new importance sampling (IS) that is tailored to quasi-Monte Carlo (QMC) integration over $\mathbb{R}^s$. IS introduces a multiplicative adjustment to the integrand by compensating the sampling from the proposal…

Numerical Analysis · Mathematics 2025-09-19 Zexin Pan , Du Ouyang , Zhijian He

We study a ferromagnetic Ising model on random graphs with a power-law degree distribution and compute the thermodynamic limit of the pressure when the mean degree is finite (degree exponent $\tau>2$), for which the random graph has a…

Probability · Mathematics 2011-07-01 Sander Dommers , Cristian Giardinà , Remco van der Hofstad

We present a systematic study of the nested sampling algorithm based on the example of the Potts model. This model, which exhibits a first order phase transition for $q>4$, exemplifies a generic numerical challenge in statistical physics:…

Computational Physics · Physics 2017-12-12 Manuel J. Pfeifenberger , Michael Rumetshofer , Wolfgang von der Linden

A computational method is presented which efficiently segments digital grayscale images by directly applying the Q-state Ising (or Potts) model. Since the Potts model was first proposed in 1952, physicists have studied lattice models to…

Data Analysis, Statistics and Probability · Physics 2017-08-18 Frank W. Bentrem

The phase behavior of Ising spin fluids is studied in the presence of an external magnetic field with the integral equation method. The calculations are performed on the basis of a soft mean spherical approximation using an efficient…

Statistical Mechanics · Physics 2016-08-31 I. P. Omelyan , I. M. Mryglod , R. Folk , W. Fenz

The branching ratio is calculated for three different models of 2d gravity, using dynamical planar phi-cubed graphs. These models are pure gravity, the D=-2 Gaussian model coupled to gravity and the single spin Ising model coupled to…

High Energy Physics - Theory · Physics 2015-06-26 M. G. Harris

A remarkable connection has been established for antiferromagnetic 2-spin systems, including the Ising and hard-core models, showing that the computational complexity of approximating the partition function for graphs with maximum degree D…

Computational Complexity · Computer Science 2014-11-05 Andreas Galanis , Daniel Stefankovic , Eric Vigoda

Probabilistic models in physics often require from the evaluation of normalized Boltzmann factors, which in turn implies the computation of the partition function Z. Getting the exact value of Z, though, becomes a forbiddingly expensive…

Computational Physics · Physics 2024-04-18 A. Prat Pou , E. Romero , J. Martí , F. Mazzanti

We give a Pfaffian formula to compute the partition function of the Ising model on any graph $G$ embedded in a closed, possibly non-orientable surface. This formula, which is suitable for computational purposes, is based on the relation…

Mathematical Physics · Physics 2020-08-26 Anh Minh Pham

A two-replica graphical representation and associated cluster algorithm is described that is applicable to ferromagnetic Ising systems with arbitrary fields. Critical points are associated with the percolation threshold of the graphical…

Statistical Mechanics · Physics 2009-10-31 Oliver Redner , Jon Machta , Lincoln Chayes

Importance sampling is a promising variance reduction technique for Monte Carlo simulation based derivative pricing. Existing importance sampling methods are based on a parametric choice of the proposal. This article proposes an algorithm…

Applications · Statistics 2009-04-14 Jan C. Neddermeyer

The ferromagnet-to-paramagnet transition of the four-dimensional random-field Ising model with Gaussian distribution of the random fields is studied. Exact ground states of systems with sizes up to 32^4 are obtained using graph theoretical…

Disordered Systems and Neural Networks · Physics 2009-11-07 Alexander K. Hartmann

In a seminal paper, Weitz showed that for two-state spin systems, such as the Ising and hardcore models from statistical physics, correlation decay on trees implies correlation decay on arbitrary graphs. The key gadget in Weitz's reduction…

Data Structures and Algorithms · Computer Science 2025-02-11 Kuikui Liu , Nitya Mani , Francisco Pernice

Bayesian methods and their implementations by means of sophisticated Monte Carlo techniques have become very popular in signal processing over the last years. Importance Sampling (IS) is a well-known Monte Carlo technique that approximates…

Computation · Statistics 2022-01-21 L. Martino , V. Elvira , G. Camps-Valls

Computing partition function is the most important statistical inference task arising in applications of Graphical Models (GM). Since it is computationally intractable, approximate methods have been used to resolve the issue in practice,…

Machine Learning · Statistics 2017-09-13 Sungsoo Ahn , Michael Chertkov , Jinwoo Shin