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The goal of this work is to find the asymptotics of the hitting probability of a distant point for the voter model on the integer lattice started from a single 1 at the origin. In dimensions 2 or 3, we obtain the precise asymptotic behavior…

Probability · Mathematics 2007-05-23 Mathieu Merle

We study a coevolving nonlinear voter model describing the coupled evolution of the states of the nodes and the network topology. Nonlinearity of the interaction is measured by a parameter q. The network topology changes by rewiring links…

Physics and Society · Physics 2017-10-10 Byungjoon Min , Maxi San Miguel

We propose a systematic method to derive the asymptotic behaviour of the persistence distribution, for a large class of stochastic processes described by a general Fokker-Planck equation in one dimension. Theoretical predictions are…

Statistical Mechanics · Physics 2009-10-31 Jean Farago

We propose a modified voter model with locally conserved magnetization and investigate its phase ordering dynamics in two dimensions in numerical simulations. Imposing a local constraint on the dynamics has the surprising effect of speeding…

Statistical Mechanics · Physics 2015-06-11 Fabio Caccioli , Luca Dall'Asta , Tobias Galla , Tim Rogers

We study a particular example of a recursive distributional equation (RDE) on the unit interval. We identify all invariant distributions, the corresponding "basins of attraction" and address the issue of endogeny for the associated…

Probability · Mathematics 2008-04-25 Saul Jacka , Marcus Sheehan

In this contribution, we construct a connection between two quantum voting models presented previously. We propose to try to determine the result of a vote from associated given opinion polls. We introduce a density operator relative to the…

Physics and Society · Physics 2024-11-22 François Dubois

The voter model has been studied extensively as a paradigmatic opinion dynamics' model. However, its ability for modeling real opinion dynamics has not been addressed. We introduce a noisy voter model (accounting for social influence) with…

Recent progress in Quality Diversity Reinforcement Learning (QD-RL) has enabled learning a collection of behaviorally diverse, high performing policies. However, these methods typically involve storing thousands of policies, which results…

Machine Learning · Computer Science 2023-06-27 Shashank Hegde , Sumeet Batra , K. R. Zentner , Gaurav S. Sukhatme

We study the persistence phenomenon in a socio-econo dynamics model using computer simulations at a finite temperature on hypercubic lattices in dimensions up to 5. The model includes a ` social\rq local field which contains the…

Physics and Society · Physics 2008-12-02 S. Jain , T. Yamano

We present novel methods for predicting the outcome of large elections. Our first algorithm uses a diffusion process to model the time uncertainty inherent in polls taken with substantial calendar time left to the election. Our second model…

Applications · Statistics 2017-04-25 Dhruv Madeka

In this paper, we study the initial value problem for infinite dimensional fractional non-autonomous reaction-diffusion equations. Applying general time-splitting methods, we prove the existence of solutions globally defined in time using…

Analysis of PDEs · Mathematics 2018-08-24 Agustín Besteiro , Diego Rial

In this paper, a linear model of diffusion processes with unknown drift and diagonal diffusion matrices is discussed. We will consider the estimation problems for unknown parameters based on the discrete time observation in high-dimensional…

Statistics Theory · Mathematics 2017-09-05 Kou Fujimori

In this paper we present an integro-differential diffusion equation for continuous time random walk that is valid for a generic waiting time probability density function. Using this equation we also study diffusion behaviors for a couple of…

Statistical Mechanics · Physics 2015-05-19 Kwok Sau Fa , K. G. Wang

Self-activation coupled to a transport mechanism results in traveling waves that describe polymerization reactions, forest fires, tumor growth, and even the spread of epidemics. Diffusion is a simple and commonly used model of particle…

Statistical Mechanics · Physics 2020-07-06 Keisuke Ishihara , Ashish B. George , Ryan Cornelius , Kirill S. Korolev

This paper studies the case of possibly high-dimensional covariates in the regression discontinuity design (RDD) analysis. In particular, we propose estimation and inference methods for the RDD models with covariate selection which perform…

Econometrics · Economics 2026-01-21 Yoichi Arai , Taisuke Otsu , Myung Hwan Seo

In the $R$-spread out, $d$-dimensional voter model, each site $x$ of $\mathbb{Z}^d$ has state (or 'opinion') 0 or 1 and, with rate 1, updates its opinion by copying that of some site $y$ chosen uniformly at random among all sites within…

Probability · Mathematics 2017-10-03 Balázs Ráth , Daniel Valesin

We estimate the distribution of random parameters in a distributed parameter model with unbounded input and output for the transdermal transport of ethanol in humans. The model takes the form of a diffusion equation with the input being the…

Optimization and Control · Mathematics 2018-08-14 Melike Sirlanci , Susan E. Luczak , Catharine E. Fairbairn , Dahyeon Kang , Ruoxi Pan , Xin Yu , I. G. Rosen

We introduce an heterogeneous nonlinear $q$-voter model with zealots and two types of susceptible voters, and study its non-equilibrium properties when the population is finite and well mixed. In this two-opinion model, each individual…

Physics and Society · Physics 2016-03-10 Andrew Mellor , Mauro Mobilia , R. K. P. Zia

We consider parameter estimation of the reaction term for a second order linear parabolic stochastic partial differential equation in two space dimensions driven by a $Q$-Wiener process under small diffusivity. We first construct an…

Statistics Theory · Mathematics 2024-04-04 Yozo Tonaki , Yusuke Kaino , Masayuki Uchida

Dealing with distribution shifts is one of the central challenges for modern machine learning. One fundamental situation is the covariate shift, where the input distributions of data change from training to testing stages while the…

Machine Learning · Computer Science 2024-05-28 Yu-Jie Zhang , Zhen-Yu Zhang , Peng Zhao , Masashi Sugiyama