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The n-vicinities method for approximate calculations of the partition function of a spin system was proposed previously. The equation of state was obtained in the most general form. In the present publication these results are adapted to…

Disordered Systems and Neural Networks · Physics 2016-06-30 Boris Kryzhanovsky , Leonid Litinskii

We develop a generalized Newton scheme IHNC for the construction of effective pair potentials for systems of interacting point-like particles.The construction is made in such a way that the distribution of the particles matches a given…

Numerical Analysis · Mathematics 2018-07-02 Fabrice Delbary , Martin Hanke , Dmitry Ivanizki

Undirected graphical models have many applications in such areas as machine learning, image processing, and, recently, psychology. Psychopathology in particular has received a lot of attention, where symptoms of disorders are assumed to…

Methodology · Statistics 2019-05-29 Lourens Waldorp , Maarten Marsman

Finite mixtures of matrix normal distributions are a powerful tool for classifying three-way data in unsupervised problems. The distribution of each component is assumed to be a matrix variate normal density. The mixture model can be…

Methodology · Statistics 2013-03-07 Cinzia Viroli

In this paper, we introduce a novel and general method for computing partition functions of solvable lattice models with free fermionic Boltzmann weights. The method is based on the ``permutation graph'' and the ``$F$-matrix'': the…

Mathematical Physics · Physics 2022-11-15 Chenyang Zhong

In this paper, we present an algorithm for computing a fundamental matrix of formal solutions of completely integrable Pfaffian systems with normal crossings in several variables. This algorithm is a generalization of a method developed for…

Symbolic Computation · Computer Science 2016-10-06 Moulay A. Barkatou , Maximilian Jaroschek , Suzy S. Maddah

Photonic Ising Machines constitute an emergent new paradigm of computation, geared towards tackling combinatorial optimization problems that can be reduced to the problem of finding the ground state of an Ising model. Spatial Photonic Ising…

In this paper we propose a new efficient interpolation tool, extremely suitable for large scattered data sets. The partition of unity method is used and performed by blending Radial Basis Functions (RBFs) as local approximants and using…

Numerical Analysis · Mathematics 2016-04-18 R. Cavoretto , A. De Rossi , E. Perracchione

In this letter we calculate the exact partition function for free bosons on the plane with lacunae. First the partition function for a plane with two spherical holes is calculated by matching exactly for the infinite set of Wilson…

High Energy Physics - Theory · Physics 2015-06-03 Ira Z. Rothstein

Recently, we developed and implemented the bond propagation algorithm for calculating the partition function and correlation functions of random bond Ising models in two dimensions. The algorithm is the fastest available for calculating…

Statistical Mechanics · Physics 2009-11-13 Y. L. Loh , E. W. Carlson , M. Y. J. Tan

A geometric formula for the zeros of the partition function of the inhomogeneous 2d Ising model was recently proposed in terms of the angles of 2d triangulations embedded in the flat 3d space. Here we proceed to an analytical check of this…

Mathematical Physics · Physics 2025-01-22 Iñaki Garay , Etera R. Livine

We develop a transfer matrix method to compute exactly the spin-spin correlation functions of Bethe lattice spin models in the external magnetic field h and for any temperature T. We first compute the correlation function for the most…

Statistical Mechanics · Physics 2009-10-31 Chin-Kun Hu , N. Sh. Izmailian

Bayesian model-based clustering is a widely applied procedure for discovering groups of related observations in a dataset. These approaches use Bayesian mixture models, estimated with MCMC, which provide posterior samples of the model…

Methodology · Statistics 2018-09-24 Ketong Wang , Michael D. Porter

We describe a method for approximating the universal scaling functions for the Ising model in a field. By making use of parametric coordinates, the free energy scaling function has a polynomial series everywhere. Its form is taken to be a…

Statistical Mechanics · Physics 2021-10-29 Jaron Kent-Dobias , James P. Sethna

The inverse Ising problem consists in inferring the coupling constants of an Ising model given the correlation matrix. The fastest methods for solving this problem are based on mean-field approximations, but which one performs better in the…

Disordered Systems and Neural Networks · Physics 2012-08-28 Federico Ricci-Tersenghi

We contribute to the mathematical theory of the design of low temperature Ising machines, a type of experimental probabilistic computing device implementing the Ising model. Encoding the output of a function in the ground state of a…

Emerging Technologies · Computer Science 2025-07-18 Andrew G. Moore , Zachary Richey , Isaac K. Martin

A simple, general and practically exact method is developed for the equilibrium properties of the macroscopic physical systems with translational symmetry. Applied to the Ising model in two and three dimension, a modest calculation gives…

Strongly Correlated Electrons · Physics 2015-05-19 S. G. Chung

We implement a full nonlinear optimization method to fit continuum states with complex Gaussians. The application to a set of regular scattering Coulomb functions allows us to validate the numerical feasibility, to explore the range of…

Computational Physics · Physics 2020-08-28 Abdallah Ammar , Arnaud Leclerc , Lorenzo Ugo Ancarani

The partition function of the finite Ising lattice with Brascamp-Kunz boundary conditions is calculated exactly in the absence of an external magnetic field and for an external field i\pi/2.

Mathematical Physics · Physics 2008-10-24 I. Lyberg

We present a novel approach to Bayesian inference and general Bayesian computation that is defined through a sequential decision loop. Our method defines a recursive partitioning of the sample space. It neither relies on gradients nor…

Machine Learning · Statistics 2021-06-10 Erik Bodin , Zhenwen Dai , Neill D. F. Campbell , Carl Henrik Ek