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Non-convergence to Unstable Equilibriums for Continuous-time and Discrete-time Stochastic Processes by Raimond, Olivier; Tarres, Pierre is a scholarly article available to read on EtoBox.

What is Non-convergence to Unstable Equilibriums for Continuous-time and Discrete-time Stochastic Processes about?

We prove non-convergence theorems towards an unstable equilibrium (or a trap) for stochastic processes. The processes we consider are continuous-time or discrete-time processes and can be pertubations of the flow generated by a vector field. Our results extend previous results given for discrete-time processes by O. Brandi{\`e}re and M. Duflo in [BD96; Duf96], by R. Pemantle in [Pem90] and by P. Tarr{\`e}s in [Tar00]. We correct and give a correct formulation to some theorems stated in [BD96; Duf96]. The method used to prove some of our theorems follow a method introduced by P. Tarr{\`e}s in [Tar00]. Finally our non-convergence theorems are applied to give correct proofs of the non-convergence towards traps for the empirical measure of vertex reinforced random walks in [BRS13] and for non-backtracking vertex reinforced random walks in [LR18].

Author

Raimond, Olivier; Tarres, Pierre

Published

2023

Language

EN