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We prove that for a sequence of finite vertex-transitive graphs of increasing sizes, the cover times are asymptotically concentrated if and only if the product of the spectral-gap and the expected cover time diverges. In fact, we prove this…

Probability · Mathematics 2019-12-24 Jonathan Hermon

Aldous [1] asked whether every graph in which the distribution of the return time of random is independent of the starting vertex must be transitive. We remark that this question can be reduced into a purely graph-theoretic one that had…

Combinatorics · Mathematics 2012-11-27 Agelos Georgakopoulos

We consider irreducible Markov chains on a finite state space. We show that the mixing time of any such chain is equivalent to the maximum, over initial states $x$ and moving large sets $(A_s)_s$, of the hitting time of $(A_s)_s$ starting…

Probability · Mathematics 2019-02-20 Perla Sousi , Peter Winkler

In this paper, we are interested in investigating the perturbation bounds for the stationary distributions for discrete-time or continuous-time Markov chains on a countable state space. For discrete-time Markov chains, two new norm-wise…

Probability · Mathematics 2012-08-27 Yuanyuan Liu

Given a discrete source distribution $\mu$ and discrete target distribution $\nu$ on a common finite state space $\mathcal{X}$, we are tasked with transporting $\mu$ to $\nu$ using a given discrete-time Markov chain $X$ with the quickest…

Probability · Mathematics 2018-07-23 Michael C. H. Choi

Consider a discrete time, ergodic Markov chain with finite state space which is started from stationarity. Fill and Lyzinski (2014) showed that, in some cases, the hitting time for a given state may be represented as a sum of a geometric…

Probability · Mathematics 2018-12-20 Fraser Daly

We study nonconcentration of hitting times for simple random walk on finite graphs. We prove that, for every connected graph with $n$ vertices, \[ \operatorname{Var}_x(\tau_y)+\mathbb E_x\tau_y \ge \frac{(\mathbb E_x\tau_y)^2}{1+\log n}, \]…

Probability · Mathematics 2026-05-19 Rafael Chiclana

We study hitting times in simple random walks on graphs, which measure the time required to reach specific target vertices. Our main result establishes a sharp lower bound for the variance of hitting times. For a simple random walk on a…

Probability · Mathematics 2024-03-25 Rafael Chiclana , Yuval Peres

We establish and generalise several bounds for various random walk quantities including the mixing time and the maximum hitting time. Unlike previous analyses, our derivations are based on rather intuitive notions of local expansion…

Probability · Mathematics 2019-03-05 Thomas Sauerwald , Luca Zanetti

A simple lemma bounds $\mathrm{s.d.}(T)/\mathbb{E} T$ for hitting times $T$ in Markov chains with a certain strong monotonicity property. We show how this lemma may be applied to several increasing set-valued processes. Our main result…

Probability · Mathematics 2016-04-22 David J. Aldous

For irreducible, time-homogeneous Markov networks, mutual linearity has recently been established for both occupation probabilities and network currents in the stationary regime as well as in the non-stationary regime in Laplace space. The…

Statistical Mechanics · Physics 2026-05-04 Julian B. Voits , Ulrich S. Schwarz

Markovian evolving graphs are dynamic-graph models where the links among a fixed set of nodes change during time according to an arbitrary Markovian rule. They are extremely general and they can well describe important dynamic-network…

Discrete Mathematics · Computer Science 2011-03-04 Andrea Clementi , Angelo Monti , Francesco Pasquale , Riccardo Silvestri

We give a characterization of the relaxation time up to an absolute constant factor, in terms of stationary expected hitting times of large sets. This resolves a conjecture of Aldous and Fill. We give a similar characterization for the…

Probability · Mathematics 2023-04-13 Jonathan Hermon

We study irreducible time-homogenous Markov chains with finite state space in discrete time. We obtain results on the sensitivity of the stationary distribution and other statistical quantities with respect to perturbations of the…

Probability · Mathematics 2007-05-23 Eilon Solan , Nicolas Vieille

Previous work has shown the effectiveness of random walk hitting times as a measure of dissimilarity in a variety of graph-based learning problems such as collaborative filtering, query suggestion or finding paraphrases. However,…

Data Structures and Algorithms · Computer Science 2013-04-17 Joel Lang , James Henderson

We obtain upper bounds (in most cases, sharp) for the hitting times of random walks on finite undirected graphs expressed as functions of the graph's number of edges. In particular, we show that the maximum hitting time for a simple random…

Combinatorics · Mathematics 2017-02-15 Dmitri Fomin

Graph-based methods for signal processing have shown promise for the analysis of data exhibiting irregular structure, such as those found in social, transportation, and sensor networks. Yet, though these systems are often dynamic,…

Machine Learning · Computer Science 2016-06-23 Nathanael Perraudin , Andreas Loukas , Francesco Grassi , Pierre Vandergheynst

We investigate the hitting times of random walks on graphs, where a hitting time is defined as the number of steps required for a random walker to move from one node to another. While much of the existing literature focuses on calculating…

Probability · Mathematics 2025-11-10 Anuraag Kumar

For any given vertices $u$ and $v$ in a graph, the hitting time of a random walk on a finite graph is the number of steps it takes for a random walk to reach vertex $v$ starting at vertex $u$. The expected value of the hitting time is the…

Combinatorics · Mathematics 2026-05-13 Aida Abiad , Yusaku Nishimura

Next to the shortest path distance, the second most popular distance function between vertices in a graph is the commute distance (resistance distance). For two vertices u and v, the hitting time H_{uv} is the expected time it takes a…

Data Structures and Algorithms · Computer Science 2015-03-13 Ulrike von Luxburg , Agnes Radl , Matthias Hein
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