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We demonstrate, by means of a convolutional neural network, that the features learned in the two-dimensional Ising model are sufficiently universal to predict the structure of symmetry-breaking phase transitions in considered systems…

Statistical Mechanics · Physics 2020-11-25 Dimitrios Bachtis , Gert Aarts , Biagio Lucini

We introduce two simple two-dimensional lattice models to study traffic flow in cities. We have found that a few basic elements give rise to the characteristic phase diagram of a first-order phase transition from a freely moving phase to a…

High Energy Physics - Lattice · Physics 2016-08-14 José A. Cuesta , Froilán C. Martínez , Juan M. Molera , Angel Sánchez Escuela

We study numerically the SU(2) Kazakov-Migdal model of `induced QCD'. In contrast to our earlier work on the subject we have chosen here {\it not} to integrate out the gauge fields but to keep them in the Monte Carlo simulation. This allows…

High Energy Physics - Lattice · Physics 2009-10-22 Sinya Aoki , Andreas Gocksch , Yue Shen

We discuss the critical properties of the three-dimensional NJL model at nonzero temperature. We show that the Z(2)-symmetric model undergoes a second order phase transition with 2d Ising exponents and its critical region is suppressed by a…

High Energy Physics - Phenomenology · Physics 2017-08-23 Costas G. Strouthos

We introduce two simple two-dimensional lattice models to study traffic flow in cities. We have found that a few basic elements give rise to the characteristic phase diagram of a first-order phase transition from a freely moving phase to a…

We apply the fidelity metric approach to analyze two recently introduced models that exhibit a quantum phase transition to a topologically ordered phase. These quantum models have a known connection to classical statistical mechanical…

Quantum Physics · Physics 2008-07-03 Damian F. Abasto , Alioscia Hamma , Paolo Zanardi

Recent years have witnessed a growing interest in using machine learning to predict and identify phase transitions in various systems. Here we adopt convolutional neural networks (CNNs) to study the phase transitions of Vicsek model,…

Biological Physics · Physics 2023-06-27 Tingting Xue , Xu Li , Xiaosong Chen , Li Chen , Zhangang Han

We review the theoretical behaviour of the total and one-particle structure factors at a quantum phase transition for temperature T=0. The predictions are compared with exact or numerical results for the transverse Ising model, the…

Statistical Mechanics · Physics 2009-11-13 C. J. Hamer

We systematically study the phase diagram of S=2 spin chain, by means of density-matrix renormalization group and exact diagonalization methods and confirm the presence of a dimer phase in the AKLT--SZH model. We find that the whole phase…

Strongly Correlated Electrons · Physics 2015-05-20 Hong-Chen Jiang , Stephan Rachel , Zheng-Yu Weng , Shou-Cheng Zhang , Zhenghan Wang

In this paper, two tests, based on CUSUM of the residuals and least squares estimation, are studied to detect in real time a change-point in a nonlinear model. A first test statistic is proposed by extension of a method already used in the…

Statistics Theory · Mathematics 2013-02-28 Gabriela Ciuperca

An algorithm for Monte Carlo simulations is proposed in which the parameter controlling the strength of the transition becomes a dynamical variable and in which efficient transitions are achieved by cluster steps. It allows to avoid the…

High Energy Physics - Lattice · Physics 2009-10-22 W. Kerler , A. Weber

We present a numerical study of 2D random-bond Potts ferromagnets. The model is studied both below and above the critical value $Q_c=4$ which discriminates between second and first-order transitions in the pure system. Two geometries are…

Statistical Mechanics · Physics 2009-10-31 Christophe Chatelain , Bertrand Berche

The recent solution to the fermion sign problem allows, for the first time, the use of cluster algorithm techniques to compute certain fermionic path integrals. To illustrate the underlying ideas behind the progress, a cluster algorithm is…

High Energy Physics - Lattice · Physics 2007-05-23 Shailesh Chandrasekharan

A cluster algorithm formulated in continuous (imaginary) time is presented for Ising models in a transverse field. It works directly with an infinite number of time-slices in the imaginary time direction, avoiding the necessity to take this…

Disordered Systems and Neural Networks · Physics 2007-05-23 H. Rieger , N. Kawashima

The Vicsek model, which was originally proposed to explain the dynamics of bird flocking, exhibits a phase transition with respect to the absolute value of the mean velocity. Although clusters of agents can be easily observed via numerical…

Statistical Mechanics · Physics 2026-01-13 Hideyuki Miyahara , Hyu Yoneki , Tsuyoshi Mizohata , Vwani Roychowdhury

Inverse problems arise in situations where data is available, but the underlying model is not. It can therefore be necessary to infer the parameters of the latter starting from the former. Statistical mechanics offers a toolbox of…

Statistical Mechanics · Physics 2025-07-04 Stefano Bae , Dario Bocchi , Luca Maria Del Bono , Luca Leuzzi

We propose a novel two-regime regression model where regime switching is driven by a vector of possibly unobservable factors. When the factors are latent, we estimate them by the principal component analysis of a panel data set. We show…

Econometrics · Economics 2022-08-11 Sokbae Lee , Yuan Liao , Myung Hwan Seo , Youngki Shin

These notes give examples of how suitably defined geometrical objects encode in their fractal structure thermal critical behavior. The emphasis is on the two-dimensional Potts model for which two types of spin clusters can be defined.…

Statistical Mechanics · Physics 2015-06-25 Wolfhard Janke , Adriaan M. J. Schakel

We investigate a phase-field-crystal model for homogeneous nucleation. Instead of solving the time evolution of a density field towards equilibrium we use a String Method to identify saddle points in phase space. The saddle points allow to…

Statistical Mechanics · Physics 2014-07-04 Rainer Backofen , Axel Voigt

The random-cluster model is a dependent percolation model that has applications in the study of Ising and Potts models. In this paper, several new results are obtained for the random-cluster model on nonamenable graphs with cluster…

Probability · Mathematics 2007-05-23 Olle Haggstrom , Johan Jonasson , Russell Lyons