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The critical behavior of Ising model on a one-dimensional network, which has long-range connections at distances $l>1$ with the probability $\Theta(l)\sim l^{-m}$, is studied by using Monte Carlo simulations. Through studying the Ising…

Pattern Formation and Solitons · Physics 2009-11-13 YunFeng Chang , Liang Sun , Xu Cai

We study graphical representations for two related models. The first model is the transverse field quantum Ising model, an extension of the original Ising model which was introduced by Lieb, Schultz and Mattis in the 1960's. The second…

Probability · Mathematics 2010-11-12 Jakob E. Björnberg

We provide a numerical study of the macroscopic model of [3] derived from an agent-based model for a system of particles interacting through a dynamical network of links. Assuming that the network remodelling process is very fast, the…

The slowing down of Moore's law has driven the development of unconventional computing paradigms, such as specialized Ising machines tailored to solve combinatorial optimization problems. In this paper, we show a new application domain for…

Emerging Technologies · Computer Science 2024-05-31 Shaila Niazi , Navid Anjum Aadit , Masoud Mohseni , Shuvro Chowdhury , Yao Qin , Kerem Y. Camsari

A hyperbolic plane can be modeled by a structure called the enhanced binary tree. We study the ferromagnetic Ising model on top of the enhanced binary tree using the renormalization-group analysis in combination with transfer-matrix…

Statistical Mechanics · Physics 2015-05-30 Seung Ki Baek , Harri Mäkelä , Petter Minnhagen , Beom Jun Kim

The earlier times of evolution of a magnetic system contain more information than we can imagine. Capturing correlation matrices G of different time evolutions of a simple testbed spin system, as the Ising model, we analyzed the density of…

Statistical Mechanics · Physics 2022-06-03 Roberto da Silva

In public opinion studies, the relationships between opinions on different topics are likely to shift based on the characteristics of the respondents. Thus, understanding the complexities of public opinion requires methods that can account…

Kinetic Ising models are powerful tools for studying the non-equilibrium dynamics of complex systems. As their behavior is not tractable for large networks, many mean-field methods have been proposed for their analysis, each based on unique…

Disordered Systems and Neural Networks · Physics 2021-05-13 Miguel Aguilera , S. Amin Moosavi , Hideaki Shimazaki

Thermodynamic properties of the ferromagnetic Ising model on the hierarchical pentagon lattice is studied by means of the tensor network methods. The lattice consists of pentagons, where 3 or 4 of them meet at each vertex. Correlation…

Statistical Mechanics · Physics 2024-07-08 Takumi Oshima , Tomotoshi Nishino

During wakefulness and deep sleep brain states, cortical neural networks show a different behavior, with the second characterized by transients of high network activity. To investigate their impact on neuronal behavior, we apply a pairwise…

Neurons and Cognition · Quantitative Biology 2017-10-30 Trang-Anh Nghiem , Olivier Marre , Alain Destexhe , Ulisse Ferrari

A lot of progress has been made recently in our understanding of the random-field Ising model thanks to large-scale numerical simulations. In particular, it has been shown that, contrary to previous statements: the critical exponents for…

Disordered Systems and Neural Networks · Physics 2018-07-10 Nikolaos G. Fytas , Victor Martin-Mayor , Marco Picco , Nicolas Sourlas

We consider testing for the parameters of Ferromagnetic Ising models. While testing for the presence of possibly sparse magnetizations, we provide a general lower bound of minimax separation rates which yields sharp results in high…

Statistics Theory · Mathematics 2019-06-04 Rajarshi Mukherjee , Gourab Ray

Contemporary work implies generative machine learning models are capable of learning the phase behavior in condensed matter systems such as the Ising model. In this Letter, we utilize a score-based modeling procedure called Thermodynamic…

Statistical Mechanics · Physics 2024-10-29 Eric R. Beyerle , Pratyush Tiwary

We consider spin models on complex networks frequently used to model social and technological systems. We study the annealed ferromagnetic Ising model for random networks with either independent edges (Erd\H{o}s-R\'enyi), or with prescribed…

Disordered Systems and Neural Networks · Physics 2021-12-07 Van Hao Can , Cristian Giardinà , Claudio Giberti , Remco van der Hofstad

The random field Ising model driven by a slowly varying uniform external field at zero temperature provides a caricature of several threshold activated systems. In this model, the non-equilibrium response of the system can be obtained…

Statistical Mechanics · Physics 2009-11-10 Prabodh Shukla

A random-field Ising model that is capable of exhibiting a rich variety of multicritical phenomena, as well as a smearing of such behavior, is investigated. The model consists of an infinite-range-interaction Ising ferromagnet in the…

Statistical Mechanics · Physics 2009-01-16 Octavio R. Salmon , Nuno Crokidakis , Fernando D. Nobre

Fitting probabilistic models to data is often difficult, due to the general intractability of the partition function. We propose a new parameter fitting method, Minimum Probability Flow (MPF), which is applicable to any parametric model. We…

Machine Learning · Computer Science 2020-07-21 Jascha Sohl-Dickstein , Peter Battaglino , Michael R. DeWeese

Several types of biological networks have recently been shown to be accurately described by a maximum entropy model with pairwise interactions, also known as the Ising model. Here we present an approach for finding the optimal mappings…

Biological Physics · Physics 2015-05-14 Jeffrey D. Fitzgerald , Tatyana O. Sharpee

We investigate quantum phase transitions in the transverse field Ising chain with algebraically decaying long-range (LR) antiferromagnetic interactions using the variational Monte Carlo method with the restricted Boltzmann machine employed…

Statistical Mechanics · Physics 2024-06-14 Jicheol Kim , Dongkyu Kim , Dong-Hee Kim

We propose an in silico molecular associative memory model for pattern learning, storage and denoising using Pairwise Markov Random Field (PMRF) model. Our PMRF-based molecular associative memory model extracts locally distributed features…

Emerging Technologies · Computer Science 2020-06-18 Dharani Punithan , Byoung-Tak Zhang