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We present a framework for obtaining explicit bounds on the rate of convergence to equilibrium of a Markov chain on a general state space, with respect to both total variation and Wasserstein distances. For Wasserstein bounds, our main tool…

Statistics Theory · Mathematics 2011-02-28 Neal Madras , Deniz Sezer

We consider a continuous time Markov chain on a countable state space and prove a joint large deviation principle for the empirical measure and the empirical flow, which accounts for the total number of jumps between pairs of states. We…

Probability · Mathematics 2015-01-19 Lorenzo Bertini , Alessandra Faggionato , Davide Gabrielli

We instigate the properties of the threshold contact process (TCP), a process showing an absorbing-state phase transition with infinitely many absorbing states, on random complex networks. The finite size scaling exponents characterizing…

Statistical Mechanics · Physics 2015-06-11 Renan S. Sander , Silvio C. Ferreira , Romualdo Pastor-Satorras

We study Markov chains with non-negative sectional curvature on finite metric spaces. Neither reversibility, nor the restriction to a particular combinatorial distance are imposed. In this level of generality, we prove that a 1-step…

Probability · Mathematics 2024-02-12 Pietro Caputo , Florentin Münch , Justin Salez

The purpose of this paper is to analyze the distribution distance between random vectors derived from the magnitude of the analytic wavelet transform of the squared envelopes of Gaussian processes and their large-scale limits. When the…

Probability · Mathematics 2024-09-05 Gi-Ren Liu

This paper develops a unified framework, based on iterated random operator theory, to analyze the convergence of constant stepsize recursive stochastic algorithms (RSAs). RSAs use randomization to efficiently compute expectations, and so…

Machine Learning · Computer Science 2021-01-06 Abhishek Gupta , William B. Haskell

In order to sample from a given target distribution (often of Gibbs type), the Monte Carlo Markov chain method consists in constructing an ergodic Markov process whose invariant measure is the target distribution. By sampling the Markov…

Probability · Mathematics 2015-06-11 Luc Rey-Bellet , Kostantinos Spiliopoulos

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 are interested in the analysis of very large continuous-time Markov chains (CTMCs) with many distinct rates. Such models arise naturally in the context of reliability analysis, e.g., of computer network performability analysis, of power…

Logic in Computer Science · Computer Science 2015-07-24 Ernst Moritz Hahn , Holger Hermanns , Ralf Wimmer , Bernd Becker

This paper is a step in the direction of understanding the behavior of non-intersecting Brownian motions on the real line, when the number of particles becomes large. Consider 2k non-intersecting Brownian motions, all starting at the…

Probability · Mathematics 2007-05-23 Mark Adler , Pierre van Moerbeke

The consensus problem -- achieving agreement among a network of agents -- is a central theme in both theory and applications. Recently, this problem has been extended from Euclidean spaces to the space of probability measures, where the…

Optimization and Control · Mathematics 2025-10-01 Pilgyu Jung , Yoon Mo Jung

We study a class of Markov chains that model the evolution of a quantum system subject to repeated measurements. Each Markov chain in this class is defined by a measure on the space of matrices. It is then given by a random product of…

Probability · Mathematics 2017-04-03 Tristan Benoist , Martin Fraas , Yan Pautrat , Clément Pellegrini

Consider a filtering process associated to a hidden Markov model with densities for which both the state space and the observation space are complete, separable, metric spaces. If the underlying, hidden Markov chain is strongly ergodic and…

Probability · Mathematics 2016-06-03 Thomas Kaijser

We study long time behavior of a discrete time weakly interacting particle system, and the corresponding nonlinear Markov process in $\mathbb{R}^d$, described in terms of a general stochastic evolution equation. In a setting where the state…

Probability · Mathematics 2014-01-16 Amarjit Budhiraja , Abhishek Pal Majumder

Perturbation theory for Markov chains addresses the question how small differences in the transitions of Markov chains are reflected in differences between their distributions. We prove powerful and flexible bounds on the distance of the…

Computation · Statistics 2017-02-27 Daniel Rudolf , Nikolaus Schweizer

We consider an individual-based spatially structured population for Darwinian evolution in an asexual population. The individuals move randomly on a bounded continuous space according to a reflected brownian motion. The dynamics involves…

Probability · Mathematics 2015-09-08 Helene Leman

We study continuous time Markov processes on graphs. The notion of frequency is introduced, which serves well as a scaling factor between any Markov time of a continuous time Markov process and that of its jump chain. As an application, we…

Probability · Mathematics 2007-05-23 Jianjun Tian , Xiao-Song Lin

We study in this paper the integration of elastic and streaming traffic on a same link in an IP network. We are specifically interested in the computation of the mean bit rate obtained by a data transfer. For this purpose, we consider that…

Networking and Internet Architecture · Computer Science 2007-08-13 Nelson Antunes , Christine Fricker , Fabrice Guillemin , Philippe Robert

Suppose that $\{X_t,\,t\ge0\}$ is a non-stationary Markov process, taking values in a Polish metric space $E$. We prove the law of large numbers and central limit theorem for an additive functional of the form $\int_0^T\psi(X_s)ds$,…

Probability · Mathematics 2012-03-26 Tomasz Komorowski , Anna Walczuk

We consider dynamics of the empirical measure of vertex neighborhood states of Markov interacting jump processes on sparse random graphs, in a suitable asymptotic limit as the graph size goes to infinity. Under the assumption of a certain…

Probability · Mathematics 2025-02-10 Juniper Cocomello , Michel Davydov , Kavita Ramanan
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