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A quantum Monte Carlo algorithm for the transverse Ising model with arbitrary short- or long-range interactions is presented. The algorithm is based on sampling the diagonal matrix elements of the power series expansion of the density…

Statistical Mechanics · Physics 2007-05-23 Anders W. Sandvik

We consider a recently introduced generalization of the Ising model in which individual spin strength can vary. The model is intended for analysis of ordering in systems comprising agents which, although matching in their binarity (i.e.,…

Statistical Mechanics · Physics 2021-09-28 Mariana Krasnytska , Bertrand Berche , Yurij Holovatch , Ralph Kenna

Experimental advances in condensed matter physics and material science have enabled ready access to atomic-resolution images, with resolution of modern tools often sufficient to extract minute details of symmetry-breaking distortions such…

Statistical Mechanics · Physics 2019-09-23 Sai Mani Prudhvi Valleti , Lukas Vlcek , Rama K. Vasudevan , Sergei V. Kalinin

We develop a fully microscopic, statistical mechanics approach to study phase transitions in Ising systems with competing interactions at different scales. Our aim is to consider orientational and positional order parameters in a unified…

Statistical Mechanics · Physics 2011-09-28 Daniel G. Barci , Daniel A. Stariolo

In this paper, we consider the Ising model on random $d$-regular graphs (with $d\ge3$) and Erd\"os-R\'enyi graphs $G(n,d/n)$ (with $d>1$) at the critical temperature. We prove that the \textit{magnetization}, i.e.\ the sum of the spins of a…

Probability · Mathematics 2026-03-31 Kyprianos-Iason Prodromidis , Allan Sly

We train a set of Restricted Boltzmann Machines (RBMs) on one- and two-dimensional Ising spin configurations at various values of temperature, generated using Monte Carlo simulations. We validate the training procedure by monitoring several…

Computational Physics · Physics 2019-08-14 Guido Cossu , Luigi Del Debbio , Tommaso Giani , Ava Khamseh , Michael Wilson

The Ising model on a $restricted$ scale-free network (SFN) has been studied employing Monte Carlo simulations. This network is described by a power-law degree distribution in the form $P(k)~k^{-\alpha}$, and is called restricted, because…

Statistical Mechanics · Physics 2023-05-24 R. A. Dumer , M. Godoy

In this paper we compute exactly the ground state energy and entropy of the dilute ferromagnetic Ising model. The two thermodynamic quantities are also computed when a magnetic field with random locations is present. The result is reached…

Disordered Systems and Neural Networks · Physics 2015-05-14 Maurizio Serva

The Ising model, in presence of an external magnetic field, is isomorphic to a model of localized interacting particles satisfying the Fermi statistics. By using this isomorphism, we construct a general solution of the Ising model which…

Strongly Correlated Electrons · Physics 2007-05-23 Ferdinando Mancini

The Monte Carlo with Absorbing Markov Chains (MCAMC) method is introduced. This method is a generalization of the rejection-free method known as the $n$-fold way. The MCAMC algorithm is applied to the study of the very low-temperature…

Statistical Mechanics · Physics 2009-11-07 M. A. Novotny

We study approximations of the partition function of dense graphical models. Partition functions of graphical models play a fundamental role is statistical physics, in statistics and in machine learning. Two of the main methods for…

Machine Learning · Computer Science 2018-02-21 Vishesh Jain , Frederic Koehler , Elchanan Mossel

Using T=0 Monte Carlo and simulated annealing simulation, we study the energy relaxation of ferromagnetic Ising and Potts models on random graphs. In addition to the expected exponential decay to a zero energy ground state, a range of…

Statistical Mechanics · Physics 2009-11-07 Pontus Svenson

In this work, we present a comparative study of the accuracy provided by the Wang-Landau sampling and the Broad Histogram method to estimate de density of states of the two dimensional Ising ferromagnet. The microcanonical averages used to…

Statistical Mechanics · Physics 2016-05-26 Alexandre Pereira Lima , Paulo Murilo Castro de Oliveira , Daniel Girardi

An introduction to the Propp-Wilson method of coupling-from-the-past for the Ising model is presented. It enables one to obtain exact samples from the equilibrium spin distribution for ferromagnetic interactions. Both uniform and random…

Materials Science · Physics 2007-05-23 Mark A. Novotny

Three dimensional Ising model ferromagnets on different lattices with nearest neighbor interactions, and on simple cubic lattices with equivalent interactions out to further neighbors, are studied numerically. The susceptibility data for…

Statistical Mechanics · Physics 2011-07-28 P. H. Lundow , I. A. Campbell

Machine learning has become a central technique for modeling in science and engineering, either complementing or as surrogates to physics-based models. Significant efforts have recently been devoted to models capable of predicting field…

Statistical Mechanics · Physics 2024-12-06 Brian H. Lee , Kat Nykiel , Ava E. Hallberg , Brice Rider , Alejandro Strachan

We consider Ising models defined on periodic approximants of aperiodic graphs. The model contains only a single coupling constant and no magnetic field, so the aperiodicity is entirely given by the different local environments of neighbours…

Statistical Mechanics · Physics 2017-08-23 Uwe Grimm , Przemyslaw Repetowicz

We investigate analytically and numerically an Ising spin model with ferromagnetic coupling defined on random graphs corresponding to Feynman diagrams of a $\phi^q$ field theory, which exhibits a mean field phase transition. We explicitly…

Statistical Mechanics · Physics 2011-04-21 Piotr Bialas , Andrzej K. Oleś

We consider a problem of model selection in high-dimensional binary Markov random fields. The usefulness of the Ising model in studying systems of complex interactions has been confirmed in many papers. The main drawback of this model is…

Methodology · Statistics 2018-12-11 Błażej Miasojedow , Wojciech Rejchel

We extend the ability of unitary quantum circuits by interfacing it with classical autoregressive neural networks. The combined model parametrizes a variational density matrix as a classical mixture of quantum pure states, where the…

Quantum Physics · Physics 2020-01-16 Jin-Guo Liu , Liang Mao , Pan Zhang , Lei Wang