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Neural network methods are increasingly applied to solve phase transition problems, particularly in identifying critical points in non-equilibrium phase transitions, offering more convenience compared to traditional methods. In this paper,…

Statistical Mechanics · Physics 2025-03-12 Feng Gao , Jianmin Shen , Shanshan Wang , Wei Li , Dian Xu

Recently, machine learning algorithms have been used remarkably to study the equilibrium phase transitions, however there are only a few works have been done using this technique in the nonequilibrium phase transitions. In this work, we use…

Statistical Mechanics · Physics 2023-07-21 M. Ali Saif , Bassam M. Mughalles

The nonequilibrium phase transition in the triplet-creation model is investigated using critical spreading and the conservative diffusive contact process. The results support the claim that at high enough diffusion the phase transition…

Statistical Mechanics · Physics 2009-11-11 Giovano O. Cardozo , Jose F. Fontanari

Machine learning (ML) has been well applied to studying equilibrium phase transition models, by accurately predicating critical thresholds and some critical exponents. Difficulty will be raised, however, for integrating ML into…

Statistical Mechanics · Physics 2024-02-27 Jianmin Shen , Wei Li , Shengfeng Deng , Tao Zhang

Large-scale Monte Carlo simulations of the bond-diluted three-dimensional 4-state Potts model are performed. The phase diagram and the physical properties at the phase transitions are studied using finite-size scaling techniques. Evidences…

Statistical Mechanics · Physics 2007-05-23 Christophe Chatelain , Bertrand Berche , Wolfhard Janke , Pierre-Emmanuel Berche

We consider a modification of the contact process incorporating higher-order reaction terms. The original contact process exhibits a non-equilibrium phase transition belonging to the universality class of directed percolation. The…

Statistical Mechanics · Physics 2009-11-11 S. Lubeck

The latest advances of statistical physics have shown remarkable performance of machine learning in identifying phase transitions. In this paper, we apply domain adversarial neural network (DANN) based on transfer learning to studying…

Statistical Mechanics · Physics 2022-07-04 Jianmin Shen , Feiyi Liu , Shiyang Chen , Dian Xu , Xiangna Chen , Shengfeng Deng , Wei Li , Gabor Papp , Chunbin Yang

The self-consistent probabilistic approach has proven itself powerful in studying the percolation behavior of interdependent or multiplex networks without tracking the percolation process through each cascading step. In order to understand…

Physics and Society · Physics 2016-05-04 Dunbiao Niu , Xin Yuan , Minhui Du , H. Eugene Stanley , Yanqing Hu

The application of machine learning in the study of phase transitions has achieved remarkable success in both equilibrium and non-equilibrium systems. It is widely recognized that unsupervised learning can retrieve phase transition…

Statistical Mechanics · Physics 2024-12-10 Dian Xu , Shanshan Wang , Weibing Deng , Feng Gao , Wei Li , Jianmin Shen

A tricritical point as a crossover between (stationary finite-wavelength) type-I$_s$ and (stationary longwave) type-II$_s$ bifurcations is identified in the study of diffusive-thermal (Turing) instability of flames propagating in a…

Pattern Formation and Solitons · Physics 2024-08-16 Prabakaran Rajamanickam , Joel Daou

Recent advances in machine learning have become increasingly popular in the applications of phase transitions and critical phenomena. By machine learning approaches, we try to identify the physical characteristics in the two-dimensional…

Disordered Systems and Neural Networks · Physics 2021-01-25 Shu Cheng , Fei He , Huai Zhang , Ka-Di Zhu , Yaolin Shi

The absorbing-state transition in the three-dimensional contact process with and without quenched randomness is investigated by means of Monte-Carlo simulations. In the clean case, a reweighting technique is combined with a careful…

Statistical Mechanics · Physics 2012-12-03 Thomas Vojta

We present detailed simulations of a generalization of the Domany-Kinzel model to 2+1 dimensions. It has two control parameters $p$ and $q$ which describe the probabilities $P_k$ of a site to be wetted, if exactly $k$ of its "upstream"…

Statistical Mechanics · Physics 2009-11-11 Peter Grassberger

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

Discontinuous percolation transitions and the associated tricritical points are manifest in a wide range of both equilibrium and non-equilibrium cooperative phenomena. To demonstrate this, we present and relate the continuous and first…

Disordered Systems and Neural Networks · Physics 2013-05-30 Golnoosh Bizhani , Maya Paczuski , Peter Grassberger

Tricritical points separate continuous and discontinuous symmetry breaking transitions. They occur in a variety of physical systems and their mathematical models. A tricritical point is used to determine a liquid-solid phase transition line…

Statistical Mechanics · Physics 2010-06-18 A. Aitta

We compare phase transition and critical phenomena of bond percolation on Euclidean lattices, nonamenable graphs, and complex networks. On a Euclidean lattice, percolation shows a phase transition between the nonpercolating phase and…

Disordered Systems and Neural Networks · Physics 2014-11-20 Takehisa Hasegawa , Tomoaki Nogawa , Koji Nemoto

We study the two-dimensional site-percolation model on a square lattice. In this paradigmatic model, sites are randomly occupied with probability $p$; a second-order phase transition from a non-percolating to a fully percolating phase…

Disordered Systems and Neural Networks · Physics 2023-11-27 Djénabou Bayo , Andreas Honecker , Rudolf A. Römer

The tricritical point, which separates first and second order phase transitions in three-dimensional superconductors, is studied in the four-dimensional Coleman-Weinberg model, and the similarities as well as the differences with respect to…

High Energy Physics - Phenomenology · Physics 2013-06-28 Miguel C. N. Fiolhais , Hagen Kleinert

We present the first detailed numerical study in three dimensions of a first-order phase transition that remains first-order in the presence of quenched disorder (specifically, the ferromagnetic/paramagnetic transition of the site-diluted…

Statistical Mechanics · Physics 2008-02-13 L. A. Fernandez , A. Gordillo-Guerrero , V. Martin-Mayor , J. J. Ruiz-Lorenzo
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