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We consider weakly interacting jump processes on time-varying random graphs with dynamically changing multi-color edges. The system consists of a large number of nodes in which the node dynamics depends on the joint empirical distribution…

Probability · Mathematics 2021-07-19 Erhan Bayraktar , Ruoyu Wu

We study the limiting behavior of interacting particle systems indexed by large sparse graphs, which evolve either according to a discrete time Markov chain or a diffusion, in which particles interact directly only with their nearest…

Probability · Mathematics 2022-05-18 Daniel Lacker , Kavita Ramanan , Ruoyu Wu

We consider a class of weakly interacting particle systems of mean-field type. The interactions between the particles are encoded in a graph sequence, i.e., two particles are interacting if and only if they are connected in the underlying…

Probability · Mathematics 2023-07-06 Gianmarco Bet , Fabio Coppini , Francesca R. Nardi

Propagation of chaos is a well-studied phenomenon and shows that weakly interacting diffusions may become independent as the system size converges to infinity. Most of the literature focuses on the case of exchangeable systems where all…

Probability · Mathematics 2021-03-09 Martin Hutzenthaler , Daniel Pieper

We consider heterogeneously interacting diffusive particle systems and their large population limit. The interaction is of mean field type with weights characterized by an underlying graphon. A law of large numbers result is established as…

Probability · Mathematics 2022-10-07 Erhan Bayraktar , Suman Chakraborty , Ruoyu Wu

We establish a functional weak law of large numbers for observable macroscopic state variables of interacting particle systems (e.g., voter and contact processes) over fast time-varying sparse random networks of interactions. We show that,…

Probability · Mathematics 2017-03-01 Augusto Almeida Santos , Soummya Kar , José M. F. Moura , João Xavier

We study diffusion and consensus dynamics in a Network of Networks model. In this model, there is a collection of sub-networks, connected to one another using a small number of links. We consider a setting where the links between networks…

Social and Information Networks · Computer Science 2020-02-17 Yuhao Yi , Anirban Das , Stacy Patterson , Bassam Bamieh , Zhongzhi Zhang

A collection of $N$-diffusing interacting particles where each particle belongs to one of $K$ different populations is considered. Evolution equation for a particle from population $k$ depends on the $K$ empirical measures of particle…

Probability · Mathematics 2015-05-06 Amarjit Budhiraja , Ruoyu Wu

We consider a collection of weakly interacting diffusion processes moving in a two-scale locally periodic environment. We study the large deviations principle of the empirical distribution of the particles' positions in the combined limit…

Probability · Mathematics 2022-11-03 Zachary Bezemek , Konstantinos Spiliopoulos

We consider a population of $N$ interacting neurons, represented by a multivariate Hawkes process: the firing rate of each neuron depends on the history of the connected neurons. Contrary to the mean-field framework where the interaction…

Probability · Mathematics 2022-02-24 Zoé Agathe-Nerine

A finite range interacting particle system on a transitive graph is considered. Assuming that the dynamics and the initial measure are invariant, the normalized empirical distribution process converges in distribution to a centered…

Mathematical Physics · Physics 2007-05-23 Paul Doukhan , Gabriel Lang , Sana Louhichi , Bernard Ycart

In this article, we study the large-population limit of interacting particle systems posed on weighted random graphs. In that aim, we introduce a general framework for the construction of weighted random graphs, generalizing the concept of…

Analysis of PDEs · Mathematics 2023-07-25 Nathalie Ayi , Nastassia Pouradier Duteil

We study expanding circle maps interacting in a heterogeneous random network. Heterogeneity means that some nodes in the network are massively connected, while the remaining nodes are only poorly connected. We provide a probabilistic…

Dynamical Systems · Mathematics 2013-08-27 Tiago Pereira , Sebastian van Strien , Jeroen S. W. Lamb

We prove limit theorems for systems of interacting diffusions on sparse graphs. For example, we deduce a hydrodynamic limit and the propagation of chaos property for the stochastic Kuramoto model with interactions determined by…

Probability · Mathematics 2020-01-01 Roberto I. Oliveira , Guilherme H. Reis , Lucas M. Stolerman

Dynamic monopolies were already defined and studied for the formulation of the phenomena of the spread of influence in social networks such as disease, opinion, adaptation of new product and etc. The elements of the network which have been…

Combinatorics · Mathematics 2018-06-08 Mitra Nemati Andavari , Manouchehr Zaker

We present our recent work on stochastic particle systems on complex networks. As a noninteracting system we first consider the diffusive motion of a random walker on heterogeneous complex networks. We find that the random walker is…

Statistical Mechanics · Physics 2007-05-23 Jae Dong Noh

In this paper, we study diffusion social learning over weakly-connected graphs. We show that the asymmetric flow of information hinders the learning abilities of certain agents regardless of their local observations. Under some…

Social and Information Networks · Computer Science 2017-01-10 Hawraa Salami , Bicheng Ying , Ali H. Sayed

We consider a system of $N$ interacting particles, described by SDEs driven by Poisson random measures, where the coefficients depend on the empirical measure of the system. Every particle jumps with a jump rate depending on its position.…

Probability · Mathematics 2025-11-13 Eva Löcherbach , Dasha Loukianova , Elisa Marini

Correlations and other collective phenomena in a schematic model of heterogeneous binary agents (individual spin-glass samples) are considered on the complete graph and also on 2d and 3d regular lattices. The system's stochastic dynamics is…

Disordered Systems and Neural Networks · Physics 2014-02-25 Imre Kondor , István Csabai , Gábor Papp , Enys Mones , Gábor Czimbalmos , Máté Csaba Sándor

We analyse diffusion dynamics on weakly-coupled networks (interconnected networks) by means of separation of time scales. Using an adiabatic approximation we reduced the system dynamics to a Markov chain with aggregated variables and…

Chaotic Dynamics · Physics 2018-12-14 Grzegorz Siudem , Janusz A. Hołyst
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