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The continuous time Markov process considered in this paper belongs to a class of population models with linear growth and catastrophes. There, the catastrophes happen at the arrival times of a Poisson process, and at each catastrophe time,…

Probability · Mathematics 2019-05-14 A. Logachov , O. Logachova , A. Yambartsev

Demographic noise causes unlimited population growth in a broad class of models which, without noise, would predict a stable finite population. We study this effect on the example of a stochastic birth-death model which includes…

Populations and Evolution · Quantitative Biology 2014-08-06 Baruch Meerson , Pavel V. Sasorov

We develop stochastic variational inference, a scalable algorithm for approximating posterior distributions. We develop this technique for a large class of probabilistic models and we demonstrate it with two probabilistic topic models,…

Machine Learning · Statistics 2013-04-24 Matt Hoffman , David M. Blei , Chong Wang , John Paisley

We consider a two-dimensional time-inhomogeneous birth-death process to model the time-evolution of fake news in a population. The two components of the process represent, respectively, (i) the number of individuals (say spreaders) who know…

Probability · Mathematics 2024-05-13 Antonio Di Crescenzo , Paola Paraggio

Large deviations for sums of i.i.d.\ random variables with stretched-exponential tails (also called Weibull or semi-exponential tails) have been well understood since the 60's, going back to Nagaev's seminal work. Many extensions in the…

Probability · Mathematics 2026-02-04 Nina Gantert , Joscha Prochno , Philipp Tuchel

Even in large systems, the effect of noise arising from when populations are initially small can persist to be measurable on the macroscale. A deterministic approximation to a stochastic model will fail to capture this effect, but it can be…

Populations and Evolution · Quantitative Biology 2024-08-13 Dylan Morris , John Maclean , Andrew J. Black

We study a variety of stochastic contact processes -- directly related to models of rumor and disease spreading -- from the viewpoint of their constants of motion, either exact or approximated. Much as in deterministic systems, constants of…

Statistical Mechanics · Physics 2026-01-19 Damián H. Zanette , Eric A. Rozán

We propose a model for diffusion of two opposite opinions. Here, the decision to be taken by each individual is a random variable which depends on the tendency of the population, as well on its own trend characteristic. The influence of the…

Probability · Mathematics 2020-01-08 Manuel González-Navarrete , Rodrigo Lambert

We studied the mutual information between a stimulus and a large system consisting of stochastic, statistically independent elements that respond to a stimulus. The Mutual Information (MI) of the system saturates exponentially with system…

Statistical Mechanics · Physics 2009-11-07 Kukjin Kang , Haim Sompolinsky

A key feature of a sequential study is that the actual sample size is a random variable that typically depends on the outcomes collected. While hypothesis testing theory for sequential designs is well established, parameter and precision…

Statistics Theory · Mathematics 2017-12-21 Ben Berckmoes , Geert Molenberghs

We propose a model of rumor spreading in which susceptible, but skeptically oriented individuals may oppose the rumor. Resistance may be implemented either by skeptical activists trying to convince spreaders to stop their activity, becoming…

Physics and Society · Physics 2020-06-24 Marco Antonio Amaral , Jeferson J. Arenzon

We consider a two-dimensional Hamiltonian system perturbed by a small diffusion term, whose coefficient is state-dependent and non-degenerate. As a result, the process consists of the fast motion along the level curves and slow motion…

Probability · Mathematics 2022-05-24 Shuo Yan

We analyze a model designed to describe the spread and accumulation of opinions in a population. Inspired by the social contagion paradigm, our model is built on the classical SIR model of Kermack and McKendrick and consists in a system of…

Analysis of PDEs · Mathematics 2024-12-16 Romain Ducasse , Samuel Tréton

The theory of large deviations deals with the probabilities of rare events (or fluctuations) that are exponentially small as a function of some parameter, e.g., the number of random components of a system, the time over which a stochastic…

Statistical Mechanics · Physics 2012-03-01 Hugo Touchette

This work continues the analysis of large deviations for randomly connected neural networks models of the brain. The originality of the model relies on the fact that the directed impact of one particle onto another depends on the state of…

Probability · Mathematics 2017-01-05 Tanguy Cabana , Jonathan Touboul

In the consensus model with bounded confidence, studied by Deffuant et al. (2000), two randomly selected people who differ not too much in their opinion both shift their opinions towards each other. Now we restrict this exchange of…

Statistical Mechanics · Physics 2009-11-10 D. Stauffer , H. Meyer-Ortmanns

The recent astonishing wide adhesion of french people to the rumor claiming `No plane did crash on the Pentagon on September the 11", is given a generic explanation in terms of a model of minority opinion spreading. Using a majority rule…

Disordered Systems and Neural Networks · Physics 2009-11-07 Serge Galam

In this paper, we consider a kind of fully coupled slow fast motion, in which the slow variable satisfies the non Lipschitz condition. We prove that the stochastic flow of the slow variable exists and moreover, satisfies the large deviation…

Probability · Mathematics 2024-09-20 Mingkun Ye , Zuozheng Zhang

A basic result of large deviations theory is Sanov's theorem, which states that the sequence of empirical measures of independent and identically distributed samples satisfies the large deviation principle with rate function given by…

Probability · Mathematics 2014-10-17 Markus Fischer

We consider a family of continuous time symmetric random walks indexed by $k\in \mathbb{N}$, $\{X_k(t),\,t\geq 0\}$. For each $k\in \mathbb{N}$ the matching random walk take values in the finite set of states…

Dynamical Systems · Mathematics 2015-06-18 Artur O. Lopes , Adriana Neumann