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Related papers: Transformations of mixed spin-class Ising systems

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We consider the problem of predicting the spin states in a kinetic Ising model when spin trajectories are observed for only a finite fraction of sites. In a Bayesian setting, where the probabilistic model of the spin dynamics is assumed to…

Disordered Systems and Neural Networks · Physics 2015-06-19 Ludovica Bachschmid Romano , Manfred Opper

This paper deals with the stochastic Ising model with a temperature shrinking to zero as time goes to infinity. A generalization of the Glauber dynamics is considered, on the basis of the existence of simultaneous flips of some spins. Such…

Probability · Mathematics 2017-01-20 Roy Cerqueti , Emilio De Santis

Randomly coupled Ising spins constitute the classical model of collective phenomena in disordered systems, with applications covering ferromagnetism, combinatorial optimization, protein folding, stock market dynamics, and social dynamics.…

Disordered Systems and Neural Networks · Physics 2016-08-24 David Dahmen , Hannah Bos , Moritz Helias

Motivated by modelling in physics and other disciplines, such as sociology and psychology, we derive the mean field of the general-spin Ising model from the variational principle of the Gibbs free energy. The general-spin Ising model has…

Statistical Mechanics · Physics 2025-09-29 Lourens Waldorp , Tuan Pham , Han L. J. van der Maas

Starting from preferences on N proposed policies obtained via questionnaires from a sample of the electorate, an Ising spin-glass model in a field can be constructed from which a political party could find the subset of the proposed…

Disordered Systems and Neural Networks · Physics 2014-10-13 M. A. Moore , Helmut G. Katzgraber

We show that the celebrated six-vertex model of statistical mechanics (along with its multistate generalizations) can be reformulated as an Ising-type model with only a two-spin interaction. Such a reformulation unravels remarkable…

Mathematical Physics · Physics 2023-01-11 Vladimir V. Bazhanov , Sergey M. Sergeev

For a very general class of probability distributions in disordered Ising spin systems, in the thermodynamical limit, we prove the following property for overlaps among real replicas. Consider the overlaps among s replicas. Add one replica…

Disordered Systems and Neural Networks · Physics 2009-10-31 Stefano Ghirlanda , Francesco Guerra

We introduce and analyze a natural class of nonlinear dynamics for spin systems such as the Ising model. This class of dynamics is based on the framework of mass action kinetics, which models the evolution of systems of entities under…

Probability · Mathematics 2024-12-24 Pietro Caputo , Alistair Sinclair

We calculate the realized volatility in the spin model of financial markets and examine the returns standardized by the realized volatility. We find that moments of the standardized returns agree with the theoretical values of standard…

Computational Finance · Quantitative Finance 2016-11-28 Tetsuya Takaishi

Several recent experiments in biology study systems composed of several interacting elements, for example neuron networks. Normally, measurements describe only the collective behavior of the system, even if in most cases we would like to…

Disordered Systems and Neural Networks · Physics 2010-10-12 Vitor Sessak

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

One of the theoretical pillars that sustain certain machine learning models are universal approximation theorems, which prove that they can approximate all functions from a function class to arbitrary precision. Independently, classical…

Disordered Systems and Neural Networks · Physics 2026-04-28 Tobias Reinhart , Gemma De les Coves

The size distribution of geometrical spin clusters is exactly found for the one dimensional Ising model of finite extent. For the values of lattice constant $\beta$ above some "critical value" $\beta_c$ the found size distribution…

Statistical Mechanics · Physics 2015-12-10 A. I. Ivanytskyi , V. O. Chelnokov

We study Ising chains with arbitrary multispin finite-range couplings, providing an explicit solution of the associated inverse Ising problem, i.e. the problem of inferring the values of the coupling constants from the correlation…

Statistical Mechanics · Physics 2011-11-16 Giacomo Gori , Andrea Trombettoni

Ising models describe the joint probability distribution of a vector of binary feature variables. Typically, not all the variables interact with each other and one is interested in learning the presumably sparse network structure of the…

Machine Learning · Computer Science 2019-07-09 Frank Nussbaum , Joachim Giesen

Species sampling processes have long served as the fundamental framework for modeling random discrete distributions and exchangeable sequences. However, data arising from distinct but related sources require a broader notion of…

Statistics Theory · Mathematics 2026-02-03 Beatrice Franzolini , Antonio Lijoi , Igor Prünster , Giovanni Rebaudo

In this communication we report the existence of a dynamic ``spin-reversal'' transition in an Ising system perturbed by a pulsed external magnetic field. The transition is achieved by tuning the strength ($h_p$) and/or the duration ($\Delta…

Condensed Matter · Physics 2015-06-25 A. Misra , B. K. Chakrabarti

We describe how the couplings in an asynchronous kinetic Ising model can be inferred. We consider two cases, one in which we know both the spin history and the update times and one in which we only know the spin history. For the first case,…

Data Analysis, Statistics and Probability · Physics 2015-06-11 Hong-Li Zeng , Mikko Alava , Erik Aurell , John Hertz , Yasser Roudi

This paper reports numerical studies of a compressible version of the Ising spin glass in two dimensions. Compressibility is introduced by adding a term that couples the spin-spin interactions and local lattice deformations to the standard…

Disordered Systems and Neural Networks · Physics 2013-05-29 Adam H. Marshall

A problem of practical significance is the analysis of large, spatially distributed data sets. The problem is more challenging for variables that follow non-Gaussian distributions. We show that the spatial correlations between variables can…

Applications · Statistics 2012-12-24 Milan Žukovič , Dionissios T. Hristopulos