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Random walks on expanders play a crucial role in Markov Chain Monte Carlo algorithms, derandomization, graph theory, and distributed computing. A desirable property is that they are rapidly mixing, which is equivalent to having a spectral…

Probability · Mathematics 2024-12-18 Sam Olesker-Taylor , Thomas Sauerwald , John Sylvester

Expansions are provided for the moments of the number of collisions $X_n$ in the $\beta(2,b)$-coalescent restricted to the set $\{1,...,n\}$. We verify that $X_n/\mathbb{E}X_n$ converges almost surely to one and that $X_n$, properly…

Statistics Theory · Mathematics 2009-09-07 Alex Iksanov , Alex Marynych , Martin Möhle

Random walks and Lorentz processes serve as fundamental models for Brownian motion. The study of random walks is a favorite object of probability theory, whereas that of Lorentz processes belongs to the theory of hyperbolic dynamical…

Probability · Mathematics 2025-01-03 Domokos Szasz

We consider n non-intersecting Brownian motion paths with p prescribed starting positions at time t=0 and q prescribed ending positions at time t=1. The positions of the paths at any intermediate time are a determinantal point process,…

Complex Variables · Mathematics 2009-07-15 Steven Delvaux , Arno B. J. Kuijlaars

Brownian motion with stochastic resetting-a process combining standard diffusion with random returns to a fixed position-has emerged as a powerful framework with applications spanning statistical physics, chemical kinetics, biology, and…

Statistical Mechanics · Physics 2025-08-18 Yihao Wang , Hanshuang Chen

We consider a family of one-dimensional self interacting walks whose dynamics characterized by a monotone weight function $w$ on $\mathbb{N}\cup \{0\}$. The weight function takes the form $w(n) = (1 + 2^p Bn^{-p} + O(n^{-1-\kappa}))^{-1}$,…

Probability · Mathematics 2025-04-01 Xiaoyu Liu , Zhe Wang

We study a Volterra Gaussian process of the form $X(t)=\int^t_0K(t,s)d{W(s)},$ where $W$ is a Wiener process and $K$ is a continuous kernel. In dimension one, we prove a law of the iterated logarithm, discuss the existence of local times…

Probability · Mathematics 2024-09-09 Olga Izyumtseva , Wasiur R. KhudaBukhsh

Let K be a compact subset of ${\mathbb R}^n$. We choose at random with uniform law a point at distance $\epsilon$ of K and start a Brownian motion (BM) from this point. We study the probability that this BM hits K for the first time at a…

Classical Analysis and ODEs · Mathematics 2019-04-22 Athanasios Batakis , Pierre Levitz , Michel Zinsmeister

In the present paper we show that the processes $X_n = \{X_n(t) \colon t \in [0,1]\}$, $n \in \mathbb{N}$, defined by $X_n(t) = \sqrt{n}C\int_0^t (-1)^{L(nu)} du$, where $L = \{L(t) \colon t \geq 0\}$ is a renewal processes whose…

Probability · Mathematics 2025-11-24 Xavier Bardina , Salim Boukfal

Bassino et al. (arXiv:1907.08517) have shown that uniform random co-graphs (graphs without induced $P_4$) of size $n$ converge to a certain non-deterministic graphon. The edge-density of this graphon is a random variable $\Lambda \in [0,1]$…

Combinatorics · Mathematics 2023-06-14 Guillaume Chapuy

Consider non-intersecting Brownian motions on the real line, starting from the origin at t=0, with a number of particles forced to reach p distinct target points at time t=1. This work shows that the transition probability, that is the…

Probability · Mathematics 2009-11-03 Mark Adler , Jonathan Delepine , Pierre van Moerbeke , Pol Vanhaecke

We establish an integration by parts formula for the semi-group in time $T > 0$ of the kinetic Brownian motion in the Euclidean plane together with its speed in the circle. The stochastic differential equation of our kinetic Brownian motion…

Probability · Mathematics 2026-03-19 Magalie Bénéfice , Michel Bonnefont , Marc Arnaudon , Delphine Féral

We prove that the empirical law of eigenvalues of Brownian motion on the Lie Group $\mathrm{GL}(N,\mathbb{C})$ converges almost surely to a deterministic probability measure, characterized by a free stochastic differential equation. This…

Probability · Mathematics 2025-11-14 Tatiana Brailovskaya , Nicholas A. Cook , Todd Kemp , Félix Parraud

We study a model of $n$ one-dimensional non-intersecting Brownian motions with two prescribed starting points at time $t=0$ and two prescribed ending points at time $t=1$ in a critical regime where the paths fill two tangent ellipses in the…

Probability · Mathematics 2010-09-14 Steven Delvaux , Arno B. J. Kuijlaars , Lun Zhang

We consider a random walk on Z^d in an i.i.d. balanced random environment, that is a random walk for which the probability to jump from x to nearest neighbor x+e is the same as to nearest neighbor x-e. Assuming that the environment is…

Probability · Mathematics 2012-07-05 Noam Berger , Jean-Dominique Deuschel

We introduce multilevel versions of Dyson Brownian motions of arbitrary parameter $\beta>0$, generalizing the interlacing reflected Brownian motions of Warren for $\beta=2$. Such processes unify $\beta$ corners processes and Dyson Brownian…

Probability · Mathematics 2016-03-10 Vadim Gorin , Mykhaylo Shkolnikov

We prove new results on lazy random walks on finite graphs. To start, we obtain new estimates on return probabilities $P^t(x,x)$ and the maximum expected hitting time $t_{\rm hit}$, both in terms of the relaxation time. We also prove a…

Probability · Mathematics 2018-07-19 Roberto I. Oliveira , Yuval Peres

In part I (math.PR/0406392) we proved for an arbitrary one-dimensional random walk with independent increments that the probability of crossing a level at a given time n is of the maximal order square root of n. In higher dimensions we call…

Probability · Mathematics 2007-05-23 Rainer Siegmund-Schultze , Heinrich von Weizsaecker

Let $G$ be a connected graph of uniformly bounded degree. A $k$ non-backtracking random walk ($k$-NBRW) $(X_n)_{n =0}^{\infty}$ on $G$ evolves according to the following rule: Given $ (X_n)_{n =0}^{s}$, at time $s+1$ the walk picks at…

Probability · Mathematics 2019-12-24 Jonathan Hermon

We consider a discrete time population model for which each individual alive at time $n$ survives independently of everybody else at time $n+1$ with probability $\beta_n$. The sequence $(\beta_n)$ is i.i.d. and constitutes our random…

Probability · Mathematics 2023-02-02 Luiz Renato Fontes , Fabio P. Machado , Rinaldo B. Schinazi