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Approximating the partition function of the ferromagnetic Ising model with general external fields is known to be #BIS-hard in the worst case, even for bounded-degree graphs, and it is widely believed that no polynomial-time approximation…

Data Structures and Algorithms · Computer Science 2021-08-27 Tyler Helmuth , Holden Lee , Will Perkins , Mohan Ravichandran , Qiang Wu

Importance sampling (IS) is a powerful Monte Carlo methodology for the approximation of intractable integrals, very often involving a target probability density function. The performance of IS heavily depends on the appropriate selection of…

Computation · Statistics 2023-06-22 Víctor Elvira , Emilie Chouzenoux , Ömer Deniz Akyildiz , Luca Martino

We present a perfect marginal sampler of the unique Gibbs measure of a spin system on $\mathbb Z^2$. The algorithm is an adaptation of a previous `lazy depth-first' approach by the authors, but relaxes the requirement of strong spatial…

Data Structures and Algorithms · Computer Science 2023-02-16 Konrad Anand , Mark Jerrum

The $q$-neighbor Ising model is investigated on homogeneous random graphs with a fraction of edges associated randomly with antiferromagnetic exchange integrals and the remaining edges with ferromagnetic ones. It is a nonequilibrium model…

Statistical Mechanics · Physics 2020-12-09 A. Krawiecki

We develop a field theoretical approach to the classical two-dimensional models, particularly to 2D Ising model (2DIM) and $XYZ$ model, which is simple to apply for calculation of various correlation functions. We calculate the partition…

Strongly Correlated Electrons · Physics 2013-07-22 Sh. A. Khachatryan , A. G. Sedrakyan

While the Ising model remains essential to understand physical phenomena, its natural connection to combinatorial reasoning makes it also one of the best models to probe complex systems in science and engineering. We bring a computational…

Computational Physics · Physics 2022-12-27 Shaan A. Nagy , Roger Paredes , Jeffrey M. Dudek , Leonardo Dueñas-Osorio , Moshe Y. Vardi

We report an effective functional form for the spin-spin correlation function of the 2D Ising model as a function of temperature and field. Although the Ising model has been well studied, no analytical result for the spin-spin correlation…

Statistical Mechanics · Physics 2013-07-29 Yan-Jiun Chen , Natalie M. Paquette , Benjamin B. Machta , James P. Sethna

The two-dimensional Ising model of a ferromagnet allows for many ways of computing its partition function and other properties. Each way reveals surprising features of what we might call Ising Matter. Moreover, the various ways would appear…

Statistical Mechanics · Physics 2020-09-28 Martin H. Krieger

We revisit classical bounds of M. E. Fisher on the ferromagnetic Ising model, and show how to efficiently use them on an arbitrary given graph to rigorously upper-bound the partition function, magnetizations, and correlations. The results…

Disordered Systems and Neural Networks · Physics 2017-05-24 Alaa Saade , Florent Krzakala , Lenka Zdeborová

We study classical Ising spin-$\frac{1}{2}$ models on the 2D square lattice with ferromagnetic or antiferromagnetic nearest-neighbor interactions, under the effect of a pure imaginary magnetic field. The complex Boltzmann weights of spin…

Statistical Mechanics · Physics 2023-06-27 Roman Krčmár , Andrej Gendiar , Ladislav Šamaj

Probabilistic models based on Restricted Boltzmann Machines (RBMs) imply the evaluation of normalized Boltzmann factors, which in turn require from the evaluation of the partition function Z. The exact evaluation of Z, though, becomes a…

Machine Learning · Computer Science 2020-07-24 Ferran Mazzanti , Enrique Romero

We present a new solution of the asymmetric two-matrix model in the large $N$ limit which only involves a saddle point analysis. The model can be interpreted as Ising in the presence of a magnetic field, on random dynamical lattices with…

Statistical Mechanics · Physics 2007-05-23 P. Zinn-Justin

Ising and Potts models are an important class of discrete probability distributions which originated from statistical physics and since then have found applications in several disciplines. Simulation from these models is a well known…

Computation · Statistics 2026-03-17 Charles C. Margossian , Chenyang Zhong , Sumit Mukherjee

In 1944 Lars Onsager published the exact partition function of the ferromagnetic Ising model on the infinite square lattice in terms of a definite integral. Only in the literature of the last decade, however, has it been recast in terms of…

Statistical Mechanics · Physics 2021-09-01 Gandhimohan M. Viswanathan

Recent inapproximability results of Sly (2010), together with an approximation algorithm presented by Weitz (2006) establish a beautiful picture for the computational complexity of approximating the partition function of the hard-core…

Discrete Mathematics · Computer Science 2016-09-14 Andreas Galanis , Daniel Stefankovic , Eric Vigoda

The exact partition function of the two-dimensional nearest neighbour Ising model pertaining to square lattices is derived for N sites in the case of a non-vanishing magnetic field.When the magnetic field is zero,the partition functions…

Statistical Mechanics · Physics 2008-01-07 G. Nandhini , M. V. Sangaranarayanan

We study mappings between distinct classical spin systems that leave the partition function invariant. As recently shown in [Phys. Rev. Lett. 100, 110501 (2008)], the partition function of the 2D square lattice Ising model in the presence…

Quantum Physics · Physics 2015-05-13 Gemma De las Cuevas , Wolfgang Dür , Maarten Van den Nest , Hans J. Briegel

The anticommuting analysis with Grassmann variables is applied to the two-dimensional Ising model in statistical mechanics. The discussion includes the transformation of the partition function into a Gaussian fermionic integral, the…

High Energy Physics - Theory · Physics 2007-05-23 V. N. Plechko

The efficient importance sampling (EIS) method is a general principle for the numerical evaluation of high-dimensional integrals that uses the sequential structure of target integrands to build variance minimising importance samplers.…

Computation · Statistics 2013-09-27 Marcel Scharth , Robert Kohn

We represent the Ising model of statistical physics by normal factor graphs in the primal and in the dual domains. By analogy with Kirchhoff's voltage and current laws, we show that in the primal normal factor graphs, the dependency among…

Information Theory · Computer Science 2018-07-24 Mehdi Molkaraie