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The voter model is a simple agent-based model to mimic opinion dynamics in social networks: a randomly chosen agent adopts the opinion of a randomly chosen neighbour. This process is repeated until a consensus emerges. Although the basic…

Statistical Mechanics · Physics 2018-06-06 Michael T. Gastner , Beáta Oborny , Máté Gulyás

We study a variant of the voter model with multiple opinions; individuals can imitate each other and also change their opinion randomly in mutation events. We focus on the case of a population with all-to-all interaction. A noise-driven…

Physics and Society · Physics 2019-08-14 Francisco Herrerías-Azcué , Tobias Galla

We present a Bayesian inference scheme for scaled Brownian motion, and investigate its performance on synthetic data for parameter estimation and model selection in a combined inference with fractional Brownian motion. We include the…

A model for anomalous transport of tracer particles diffusing in complex media in two dimensions is proposed. The model takes into account the characteristics of persistent motion that active bath transfer to the tracer, thus the model…

Statistical Mechanics · Physics 2025-07-24 Francisco J. Sevilla , Adriano Valdés-Gómez , Alexis Torres-Carbajal

We define a stochastic reaction-diffusion process that describes a consensus formation in a non-sedentary population. The process is a diffusive version of the Majority Vote model, where the state update follows two stages: in the first…

Statistical Mechanics · Physics 2022-03-14 J. R. S. Lima , F. W. S. Lima , T. F. A. Alves , G. A. Alves , A. Macedo-Filho

This letter introduces a formalism for modeling time-variant channels for diffusive molecular communication systems. In particular, we consider a fluid environment where one transmitter nano-machine and one receiver nano-machine are…

Information Theory · Computer Science 2017-03-08 Arman Ahmadzadeh , Vahid Jamali , Adam Noel , Robert Schober

The origin of the long-range memory in the non-equilibrium systems is still an open problem as the phenomenon can be reproduced using models based on Markov processes. In these cases a notion of spurious memory is introduced. A good example…

Statistical Finance · Quantitative Finance 2017-08-01 Vygintas Gontis , Aleksejus Kononovicius

The voter model is a paradigm of ordering dynamics. At each time step, a random node is selected and copies the state of one of its neighbors. Traditionally, this state has been considered as a binary variable. Here, we relax this…

Statistical Mechanics · Physics 2015-06-05 Michele Starnini , Andrea Baronchelli , Romualdo Pastor-Satorras

In this work we propose a new class of long-memory models with time-varying fractional parameter. In particular, the dynamics of the long-memory coefficient, $d$, is specified through a stochastic recurrence equation driven by the score of…

Methodology · Statistics 2018-12-19 Luisa Bisaglia , Matteo Grigoletto

Models of imitation and herding behavior often underestimate the role of individualistic actions and assume symmetric boundary conditions. However, real-world systems (e.g., electoral processes) frequently involve asymmetric boundaries. In…

Statistical Mechanics · Physics 2025-12-03 Rytis Kazakevičius , Aleksejus Kononovicius

We present a full stochastic description of the pair approximation scheme to study binary-state dynamics on heterogeneous networks. Within this general approach, we obtain a set of equations for the dynamical correlations, fluctuations and…

Physics and Society · Physics 2018-11-05 A. F. Peralta , A. Carro , M. San Miguel , R. Toral

It is well known that on long time scales the behaviour of tracer particles diffusing in a cellular flow is effectively that of a Brownian motion. This paper studies the behaviour on "intermediate" time scales before diffusion sets in.…

Analysis of PDEs · Mathematics 2016-09-09 Gautam Iyer , Alexei Novikov

Fractional Brownian motion is a Gaussian stochastic process with stationary, long-time correlated increments and is frequently used to model anomalous diffusion processes. We study numerically fractional Brownian motion confined to a finite…

Statistical Mechanics · Physics 2019-03-22 T. Guggenberger , G. Pagnini , T. Vojta , R. Metzler

We consider a discrete-time voter model process on a set of nodes, each being in one of two states, either 0 or 1. In each time step, each node adopts the state of a randomly sampled neighbor according to sampling probabilities, referred to…

Optimization and Control · Mathematics 2022-11-28 Milan Vojnovic , Kaifang Zhou

For the voter model, we study the effect of a memory-dependent transition rate. We assume that the transition of a spin into the opposite state decreases with the time it has been in its current state. Counter-intuitively, we find that the…

Disordered Systems and Neural Networks · Physics 2009-11-13 Hans-Ulrich Stark , Claudio J. Tessone , Frank Schweitzer

The role of memory is crucial in determining the properties of many dynamical processes in statistical physics. We show that the simple addition of memory, in the form of noise reduction, modifies the overall scaling behavior of the voter…

Statistical Mechanics · Physics 2007-05-23 Luca Dall'Asta , Claudio Castellano

Fractional Brownian motion and the fractional Langevin equation are models of anomalous diffusion processes characterized by long-range power-law correlations in time. We employ large-scale computer simulations to study these models in two…

Statistical Mechanics · Physics 2021-04-22 Thomas Vojta , Alex Warhover

The adaptive voter model allows for studying the interplay between homophily, the tendency of like-minded individuals to attract each other, and social influence, the tendency for connected individuals to influence each other. However, it…

Physics and Society · Physics 2023-03-21 Nikos Papanikolaou , Renaud Lambiotte , Giacomo Vaccario

Stochastic process exhibiting power-law slopes in the frequency domain are frequently well modeled by fractional Brownian motion (fBm). In particular, the spectral slope at high frequencies is associated with the degree of small-scale…

Methodology · Statistics 2017-09-13 J. M. Lilly , A. M. Sykulski , J. J Early , S. C. Olhede

Switching dynamical systems provide a powerful, interpretable modeling framework for inference in time-series data in, e.g., the natural sciences or engineering applications. Since many areas, such as biology or discrete-event systems, are…

Machine Learning · Computer Science 2021-09-30 Lukas Köhs , Bastian Alt , Heinz Koeppl