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We study Barkhausen noise in a diluted two-dimensional Ising model with the extended domain wall and weak random fields occurring due to coarse graining. We report two types of scaling behavior corresponding to (a) low disorder regime where…

Statistical Mechanics · Physics 2009-10-31 Bosiljka Tadić

A method to study strongly interacting quantum many-body systems at and away from criticality is proposed. The method is based on a MERA-like tensor network that can be efficiently and reliably contracted on a noisy quantum computer using a…

Quantum Physics · Physics 2017-11-22 Isaac H. Kim , Brian Swingle

Nonlinear complex network-coupled systems typically have multiple stable equilibrium states. Following perturbations or due to ambient noise, the system is pushed away from its initial equilibrium and, depending on the direction and the…

Adaptation and Self-Organizing Systems · Physics 2023-06-08 Melvyn Tyloo

Imbibition phenomena have been widely used experimentally and theoretically to study the kinetic roughening of interfaces. We critically discuss the existing experiments and some associated theoretical approaches on the scaling properties…

Disordered Systems and Neural Networks · Physics 2009-10-31 M. Dube , M. Rost , M. Alava

Stochastic differential equations (SDEs) are a ubiquitous modeling framework that finds applications in physics, biology, engineering, social science, and finance. Due to the availability of large-scale data sets, there is growing interest…

Machine Learning · Statistics 2025-03-04 Ziheng Guo , James Greene , Ming Zhong

We study the effects of uniform time delays on the extreme fluctuations in stochastic synchronization and coordination problems with linear couplings in complex networks. We obtain the average size of the fluctuations at the nodes from the…

Statistical Mechanics · Physics 2015-12-15 D. Hunt , F. Molnar , B. K. Szymanski , G. Korniss

Smoothed analysis is a framework suggested for mediating gaps between worst-case and average-case complexities. In a recent work, Dinitz et al.~[Distributed Computing, 2018] suggested to use smoothed analysis in order to study dynamic…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-09-29 Uri Meir , Ami Paz , Gregory Schwartzman

This article presents results on the concentration properties of the smoothing and filtering distributions of some partially observed chaotic dynamical systems. We show that, rather surprisingly, for the geometric model of the Lorenz…

Statistics Theory · Mathematics 2018-01-30 Daniel Paulin , Ajay Jasra , Dan Crisan , Alexandros Beskos

We study the prisoner's dilemma model with a noisy imitation evolutionary dynamics on directed out-homogeneous and uncorrelated directed random networks. An heterogeneous pair mean-field approximation is presented showing good agreement…

Physics and Society · Physics 2017-01-04 A. L. Ferreira , A. Lipowski , T. B. Pedro , M. Santos , W. Figueiredo

We study spontaneous imbibition using a phase field model in a two dimensional system with a dichotomic quenched noise. By imposing a constant pressure $\mu_{a}<0$ at the origin, we study the case when the interface advances at low…

Disordered Systems and Neural Networks · Physics 2009-11-11 M. Pradas , A. Hernández-Machado

The dynamics of well-mixed biological populations is usually studied by mean-field methods and weak-noise expansions. Similar methods have been applied also in spatially extended problems, relying on the fact that these populations are…

Statistical Mechanics · Physics 2015-03-17 Luca Dall'Asta , Fabio Caccioli , Deborah Beghè

A small-world network (SW) of similar phase oscillators, interacting according to the Kuramoto model is studied numerically. It is shown that deterministic Kuramoto dynamics on the SW networks has various stable stationary states. This can…

Disordered Systems and Neural Networks · Physics 2013-04-11 Reihaneh Kouhi Esfahani , Farhad Shahbazi , Keivan Aghababaei Samani

We highlight a fundamental ill-posedness issue for nonlinear stochastic wave equations driven by a fractional noise. Namely, if the noise becomes too rough (i.e., the sum of its Hurst indexes becomes too small), then there is essentially no…

Probability · Mathematics 2021-12-17 Aurélien Deya

The dynamics of noise-resilient Boolean networks with majority functions and diverse topologies is investigated. A wide class of possible topological configurations is parametrized as a stochastic blockmodel. For this class of networks, the…

Disordered Systems and Neural Networks · Physics 2012-01-11 Tiago P. Peixoto

We propose a simple discrete model to study the nonequilibrium fluctuations of two locally coupled 1+1 dimensional systems (interfaces). Measuring numerically the tilt-dependent velocity we construct a set of stochastic continuum equations…

Condensed Matter · Physics 2009-10-22 Albert-László Barabási

The World Trade Web (WTW) is a weighted network whose nodes correspond to countries with edge weights reflecting the value of imports and/or exports between countries. In this paper we introduce to this macroeconomic system the notion of…

General Finance · Quantitative Finance 2015-03-19 N. Foti , S. Pauls , Daniel N. Rockmore

We study the evolution of a random weighted network with complex nonlinear dynamics at each node, whose activity may cease as a result of interactions with other nodes. Starting from a knowledge of the micro-level behaviour at each node, we…

Statistical Mechanics · Physics 2007-05-23 Sitabhra Sinha , Sudeshna Sinha

Oscillator networks display intricate synchronization patterns. Determining their stability typically requires incorporating the symmetries of the network coupling. Going beyond analyses that appeal only to a network's automorphism group,…

Dynamical Systems · Mathematics 2020-12-14 J. Emenheiser , A. Salova , J. Snyder , J. P. Crutchfield , R. M. D'Souza

From spiking activity in neuronal networks to force chains in granular materials, the behavior of many real-world systems depends on a network of both strong and weak interactions. These interactions give rise to complex and higher-order…

Quantitative Methods · Quantitative Biology 2021-01-12 Ann S. Blevins , Jason Z. Kim , Danielle S. Bassett

We provide a general framework for studying recurrent neural networks (RNNs) trained by injecting noise into hidden states. Specifically, we consider RNNs that can be viewed as discretizations of stochastic differential equations driven by…

Machine Learning · Statistics 2021-12-02 Soon Hoe Lim , N. Benjamin Erichson , Liam Hodgkinson , Michael W. Mahoney