The Kolmogorov forward equations, information theory and mathematical modeling of the Ising model

Document Type : Research Paper

Authors

Department of Mathematics, University of Kashan, Kashan, Iran.

Abstract

In this paper, one of the applications of the Kolmogorov forward equations in solving the equations in the Ising model will be analyzed. The limiting distribution and the stationary distribution of the corresponding birth and death process will be calculated. The Ising model is one of the famous physical models that is used in other sciences. The three special cases of the Ising model, i.e., the square grid, horizontal and circular systems will be analyzed and examined. We will show that in general Ising models based on Boltzmann stationary distribution, MLE and MME to estimate for the reverse temperature characteristic of the heat baths are the same. The equation related to finding MLE and a MME cannot be solved analytically, so these estimates will be calculated using the technique of fitting a linear regression model. By the way, it will be observed that, the entropy values for the grid system, are smaller than corresponding values in the horizontal and circular systems. Then, a general case for the convexity of the entropy of the Boltzmann probability function will be introduced. Also, considering an Ising model on two and three points, where the points take values independently and follow a Markov chain, the stationary distribution as well as the Boltzmann probability function, its induced probability function and MLE for parameter will be calculated. Finally, we will review Metropolis-Hastings algorithm and Gibbs sampling to simulating the one-dimensional and two-dimensional Ising model and also Potts model in ‎R software‎. Finally, we will compare the ‎‎ grid, horizontal and circular systems. The induced probability vectors by system energies will be found for the three systems. The entropy of these three induced probability vectors and the entropy of Boltzmann probability and their two-by-two Kullback-Leibler divergences will be plotted and compared as a function of the parameter.

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Articles in Press, Accepted Manuscript
Available Online from 21 April 2025
  • Receive Date: 27 August 2024
  • Revise Date: 29 March 2025
  • Accept Date: 19 April 2025