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A kinetic Ising model is analyzed where spin variables correspond to lattice cells with mobile or immobile particles. Introducing additional restrictions for the flip processes according to the n-spin facilitated kinetic Ising model and…

Disordered Systems and Neural Networks · Physics 2009-10-31 B. Zheng , M. Schulz , S. Trimper

We study an effective spin model derived perturbatively from random transverse-field Ising model on the pyrochlore lattice. The model consists of spin-configurations on the pyrochlore lattice, restricted to the spin-ice subspace, with spins…

Strongly Correlated Electrons · Physics 2020-05-27 Anirudha Menon , Tom Pardini , Rajiv R. P. Singh

The main purpose of percolation theory is to model phase transitions in a variety of random systems, which is highly valuable in fields related to materials physics, biology, or otherwise unrelated areas like oil extraction or even quantum…

Statistical Mechanics · Physics 2025-01-28 Daniel García Solla

A lattice-based model for continuum percolation is applied to the case of randomly located, partially aligned sticks with unequal lengths in 2D which are allowed to cross each other. Results are obtained for the critical number of sticks…

Statistical Mechanics · Physics 2024-10-17 Avik P. Chatterjee , Yuri Yu. Tarasevich

In this article, we review the interdisciplinary techniques (borrowed from physics, mathematics, statistics, machine-learning, etc.) and methodological framework that we have used to understand climate systems, which serve as examples of…

Data Analysis, Statistics and Probability · Physics 2024-05-29 Alka Yadav , Sourish Das , Anirban Chakraborti

We employ the microcanonical inflection-point analysis method, developed for the systematic identification and classification of phase transitions in systems of any size, to study the two-dimensional Ising model at various lattice sizes and…

Statistical Mechanics · Physics 2023-06-30 Kedkanok Sitarachu , Michael Bachmann

We have found a simple criterion which allows for the straightforward determination of the order-disorder critical temperatures. The method reproduces exactly results known for the two dimensional Ising, Potts and $Z(N<5)$ models. It also…

High Energy Physics - Lattice · Physics 2009-10-22 J. Wosiek

We study the zero-temperature stochastic Ising model on some connected planar quasi-transitive graphs, which are invariant under rotation and translation. The initial spin configuration is distributed according to a Bernoulli product…

Probability · Mathematics 2023-10-23 Emilio De Santis , Leonardo Lelli

Signatures of critical behaviour in nuclear fragmentation are often based on arguments from percolation theory. We demonstrate with general thermodynamic considerations and studies of the Ising model that the reliance on percolation as a…

Nuclear Experiment · Physics 2007-05-23 W. F. J. Mueller , ALADIN collaboration

In this paper, we investigate the invasion percolation (IP) in imperfect support in which the configuration of imperfections is considered to be correlated. Three lattice models were engaged to realize this pattern: site percolation, Ising…

Statistical Mechanics · Physics 2022-01-05 M. N. Najafi , S. Tizdast , J. Cheraghalizadeh , H. Dashti N

Finding a ground state of a given Hamiltonian of an Ising model on a graph $G=(V,E)$ is an important but hard problem. The standard approach for this kind of problem is the application of algorithms that rely on single-spin-flip Markov…

The critical properties of the stochastic susceptible-exposed-infected model on a square lattice is studied by numerical simulations and by the use of scaling relations. In the presence of an infected individual, a susceptible becomes…

Statistical Mechanics · Physics 2016-08-08 Alexander H. O. Wada , Tânia Tomé , Mário J. de Oliveira

The lattice spin model, with nearest neighbor ferromagnetic exchange and long range dipolar interaction, is studied by the method of time series for observables based on cluster configurations and associated partitions, such as Shannon…

Disordered Systems and Neural Networks · Physics 2009-11-10 M. Casartelli , L. Dall'Asta , E. Rastelli , S. Regina

These lecture notes give an introduction to the theory of interacting particle systems. The main subjects are the construction using generators and graphical representations, the mean field limit, stochastic order, duality, and the relation…

Probability · Mathematics 2025-11-10 Jan M. Swart

In these notes, the application of Feynman's sum-over-paths approach to thermal phase transitions is discussed. The paradigm of such a spacetime approach to critical phenomena is provided by the high-temperature expansion of spin models.…

Statistical Mechanics · Physics 2016-11-23 Wolfhard Janke , Adriaan M. J. Schakel

We study a simple model of the stochastic information filtering, in a randomly organized information system. For simplest versions of the model it appears to be possible to describe the filtering dynamics in terms of the master equations.…

Disordered Systems and Neural Networks · Physics 2009-11-07 I. S. Manida , Yu. M. Pis'mak

The magnetically ordered, low temperature phase of Ising ferro- magnets is manifested within the associated Fortuin-Kasteleyn (FK) random cluster representation by the occurrence of a single positive density percolating cluster. In this…

Statistical Mechanics · Physics 2008-05-08 J. Machta , C. M. Newman , D. L. Stein

Monte Carlo simulations using entropic sampling to estimate the number of configurations of a given energy are a valuable alternative to traditional methods. We introduce {\it tomographic} entropic sampling, a scheme which uses multiple…

Statistical Mechanics · Physics 2015-05-28 Ronald Dickman , A. G. Cunha-Netto

We present a new approach to a classical problem in statistical physics: estimating the partition function and other thermodynamic quantities of the ferromagnetic Ising model. Markov chain Monte Carlo methods for this problem have been…

Statistical Mechanics · Physics 2013-06-20 Amanda Streib , Noah Streib , Isabel Beichl , Francis Sullivan

In-context learning (ICL) emerges as a promising capability of large language models (LLMs) by providing them with demonstration examples to perform diverse tasks. However, the underlying mechanism of how LLMs learn from the provided…

Computation and Language · Computer Science 2023-12-20 Lean Wang , Lei Li , Damai Dai , Deli Chen , Hao Zhou , Fandong Meng , Jie Zhou , Xu Sun