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In this paper we investigate a model of consensus decision making [Hartnett A. T., et al., Phys. Rev. Lett., 2016, 116, 038701] following a statistical physics approach presented in [Sarkanych P., et al., Phys. Biol., 2023, 20, 045005].…

Statistical Mechanics · Physics 2024-09-25 P. Sarkanych , Yu. Sevinchan , M. Krasnytska , P. Romanczuk , Yu. Holovatch

Using molecular dynamics simulation, we investigate the slow dynamics of a supercooled binary mixture of soft particles interacting with a generalized Hertzian potential. At low density, it displays typical slow dynamics near its glass…

Soft Condensed Matter · Physics 2016-10-18 Ryoji Miyazaki , Takeshi Kawasaki , Kunimasa Miyazaki

Plastically deforming crystals exhibit scale-free fluctuations that are similar to those observed in driven disordered elastic systems close to depinning, but the nature of the yielding critical point is still debated. Here, we study the…

Statistical Mechanics · Physics 2018-01-03 Markus Ovaska , Arttu Lehtinen , Mikko J. Alava , Lasse Laurson , Stefano Zapperi

Most of the analytical studies on spin glasses are performed by using mean-field theory and renormalization group analysis. Analytical studies on finite-dimensional spin glasses are very challenging. In this short note, a possible exten-…

Disordered Systems and Neural Networks · Physics 2018-01-17 Masayuki Ohzeki , Yuta Kudo , Kazuyuki Tanaka

We realize an extensive numerical study of the Naming Game model with a noise term which accounts for perturbations. This model displays a non-equilibrium phase transition between an absorbing ordered consensus state, which occurs for small…

Physics and Society · Physics 2016-11-15 E. Brigatti , A. Hernández

The Constraint Satisfaction Problem (CSP) framework offers a simple and sound basis for representing and solving simple decision problems, without uncertainty. This paper is devoted to an extension of the CSP framework enabling us to deal…

Artificial Intelligence · Computer Science 2013-02-21 Helene Fargier , Jerome Lang , Roger Martin-Clouaire , Thomas Schiex

LECTURE GIVEN AT TH2002. Given a set of Boolean variables, and some constraints between them, is it possible to find a configuration of the variables which satisfies all constraints? This problem, which is at the heart of combinatorial…

Disordered Systems and Neural Networks · Physics 2009-11-07 Marc Mezard

This paper investigates the reconfiguration variant of the Constraint Satisfaction Problem (CSP), referred to as the Reconfiguration CSP (RCSP). Given a CSP instance and two of its solutions, RCSP asks whether one solution can be…

Data Structures and Algorithms · Computer Science 2026-03-06 Kei Kimura

We study the critical behavior of Boolean variables on scale-free networks with competing interactions (Ising spin glasses). Our analytical results for the disorder-network-decay-exponent phase diagram are verified using Monte Carlo…

Disordered Systems and Neural Networks · Physics 2012-09-17 Helmut G. Katzgraber , Katharina Janzen , Creighton K. Thomas

Cold atom developments suggest the prospect of measuring scaling properties and long-range fluctuations of continuous phase transitions at zero-temperature. We discuss the conditions for characterizing the phase separation of Bose-Einstein…

Statistical Mechanics · Physics 2012-02-16 D. H. Santamore , Eddy Timmermans

A variational model to simultaneously treat Stress-Driven Rearrangement Instabilities, such as boundary discontinuities, internal cracks, external filaments, edge delamination, wetting, and brittle fractures, is introduced. The model is…

Analysis of PDEs · Mathematics 2020-06-24 Shokhrukh Yu. Kholmatov , Paolo Piovano

We introduce a solvable spherical model of coupled oscillators with fully random interactions and distributed natural frequencies. Using the dynamical mean-field theory, we derive self-consistent equations for the steady-state response and…

Disordered Systems and Neural Networks · Physics 2026-04-07 Harukuni Ikeda

Systems with quenched disorder possess complex energy landscapes that are challenging to explore under the conventional Monte Carlo method. In this work, we implement an efficient entropy sampling scheme for accurate computation of the…

Disordered Systems and Neural Networks · Physics 2025-05-08 Yi Liu , Ding Wang , Xin Wang , Dao-Xin Yao , Lei-Han Tang

The dynamical glass transition is typically taken to be the temperature at which a glassy liquid is no longer able to equilibrate on experimental timescales. Consequently, the physical properties of these systems just above or below the…

Soft Condensed Matter · Physics 2017-03-08 Samuel S. Schoenholz , Ekin D. Cubuk , Efthimios Kaxiras , Andrea J. Liu

Tree-based ensemble methods, as Random Forests and Gradient Boosted Trees, have been successfully used for regression in many applications and research studies. Furthermore, these methods have been extended in order to deal with uncertainty…

Machine Learning · Computer Science 2018-11-20 Myriam Tami , Marianne Clausel , Emilie Devijver , Adrien Dulac , Eric Gaussier , Stefan Janaqi , Meriam Chebre

We study the evolution of percolation with freezing. Specifically, we consider cluster formation via two competing processes: irreversible aggregation and freezing. We find that when the freezing rate exceeds a certain threshold, the…

Statistical Mechanics · Physics 2007-05-23 E. Ben-Naim , P. L. Krapivsky

Global changes of states are of crucial importance in optimization algorithms. We review some heuristic algorithms in which global updates are realized by a sort of real-space renormalization group transformation. Emphasis is on the…

Disordered Systems and Neural Networks · Physics 2009-10-31 Naoki Kawashima

The random XORSAT problem deals with large random linear systems of Boolean variables. The difficulty of such problems is controlled by the ratio of number of equations to number of variables. It is known that in some range of values of…

Disordered Systems and Neural Networks · Physics 2016-08-16 Thierry Mora , Marc Mézard

We introduce a version of the cavity method for diluted mean-field spin models that allows the computation of thermodynamic quantities similar to the Franz-Parisi quenched potential in sparse random graph models. This method is developed in…

Disordered Systems and Neural Networks · Physics 2015-05-13 Federico Ricci-Tersenghi , Guilhem Semerjian

When a liquid is cooled below its melting temperature, if crystallization is avoided, it forms a glass. This phenomenon, called glass transition, is characterized by a marked increase of viscosity, about 14 orders of magnitude, in a narrow…

Disordered Systems and Neural Networks · Physics 2008-08-23 Simone Capaccioli , Giancarlo Ruocco , Francesco Zamponi