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Using spectral graph theory, we show how to obtain inequalities for the number of walks in graphs from nonnegative polynomials and present a new family of such inequalities.

Discrete Mathematics · Computer Science 2023-03-28 Nadja Willenborg , Sven Kosub

This work studies the relation between two graph parameters, $\rho$ and $\Lambda$. For an undirected graph $G$, $\rho(G)$ is the growth rate of its universal covering tree, while $\Lambda(G)$ is a weighted geometric average of the vertex…

Combinatorics · Mathematics 2026-05-01 Idan Eisner , Shlomo Hoory

We study random walks on the integers mod $G_n$ that are determined by an integer sequence $\{ G_n \}_{n \geq 1}$ generated by a linear recurrence relation. Fourier analysis provides explicit formulas to compute the eigenvalues of the…

Probability · Mathematics 2017-10-12 Caprice Stanley , Seth Sullivant

We show bounds on total variation and $L^{\infty}$ mixing times, spectral gap and magnitudes of the complex valued eigenvalues of a general (non-reversible non-lazy) Markov chain with a minor expansion property. This leads to the first…

Combinatorics · Mathematics 2009-04-03 Ravi Montenegro

We give a simple combinatorial proof of a formula that extends a result by Grigorchuk (rediscovered by Cohen) relating cogrowth and spectral radius of random walks. Our main result is an explicit equation determining the number of `bumps'…

Combinatorics · Mathematics 2008-06-05 Laurent Bartholdi

A distinguishing property of communities in networks is that cycles are more prevalent within communities than across communities. Thus, the detection of these communities may be aided through the incorporation of measures of the local…

Social and Information Networks · Computer Science 2019-10-15 Behnaz Moradi-Jamei , Heman Shakeri , Pietro Poggi-Corradini , Michael J. Higgins

A distinguishing property of communities in networks is that cycles are more prevalent within communities than across communities. Thus, the detection of these communities may be aided through the incorporation of measures of the local…

Social and Information Networks · Computer Science 2019-10-21 Behnaz Moradi , Heman Shakeri , Pietro Poggi-Corradini , Michael Higgins

Graph vertex embeddings based on random walks have become increasingly influential in recent years, showing good performance in several tasks as they efficiently transform a graph into a more computationally digestible format while…

Machine Learning · Statistics 2021-07-22 Dominik Kloepfer , Angelica I. Aviles-Rivero , Daniel Heydecker

Importance sampling algorithms for heavy-tailed random walks are considered. Using a specification with algorithms based on mixtures of the original distribution with some other distribution, sufficient conditions for obtaining bounded…

Probability · Mathematics 2009-09-21 Henrik Hult , Jens Svensson

Mixing of finite time-homogeneous Markov chains is well understood nowadays, with a rich set of techniques to estimate their mixing time. In this paper, we study the mixing time of random walks in dynamic random environments. To that end,…

Probability · Mathematics 2023-09-27 Raphael Erb

We consider the simple random walk on the graph corresponding to a Penrose tiling. We prove that the path distribution of the walk converges weakly to that of a non-degenerate Brownian motion for almost every Penrose tiling with respect to…

Probability · Mathematics 2014-07-08 Zs. Bartha , A. Telcs

Accurately analyzing graph properties of social networks is a challenging task because of access limitations to the graph data. To address this challenge, several algorithms to obtain unbiased estimates of properties from few samples via a…

Social and Information Networks · Computer Science 2020-07-14 Kazuki Nakajima , Kazuyuki Shudo

Consider a discrete-time quantum walk on the $N$-cycle subject to decoherence both on the coin and the position degrees of freedom. By examining the evolution of the density matrix of the system, we derive some new conclusions about the…

Quantum Physics · Physics 2011-07-20 Chaobin Liu , Nelson Petulante

Hypergraph has been selected as a powerful candidate for characterizing higher-order networks and has received increasing attention in recent years. In this article, we study random walks with resetting on hypergraph by utilizing spectral…

Social and Information Networks · Computer Science 2025-05-08 Fei Ma , Xincheng Hu , Haobin Shi , Wei Pan , Ping Wang

A second-order random walk on a graph or network is a random walk where transition probabilities depend not only on the present node but also on the previous one. A notable example is the non-backtracking random walk, where the walker is…

Probability · Mathematics 2021-12-28 Dario Fasino , Arianna Tonetto , Francesco Tudisco

A randomly walking quantum particle evolving by Schr\"odinger's equation searches for a unique marked vertex on the "simplex of complete graphs" in time $\Theta(N^{3/4})$. In this paper, we give a weighted version of this graph that…

Quantum Physics · Physics 2015-09-22 Thomas G. Wong

We prove results for random walks in dynamic random environments which do not require the strong uniform mixing assumptions present in the literature. We focus on the "environment seen from the walker"-process and in particular its…

Probability · Mathematics 2016-10-06 Stein Andreas Bethuelsen , Florian Völlering

We study the discrete quantum walk on a regular graph $X$ that assigns negative identity coins to marked vertices $S$ and Grover coins to the unmarked ones. We find combinatorial bases for the eigenspaces of the transtion matrix, and derive…

Combinatorics · Mathematics 2024-12-19 Amulya Mohan , Hanmeng Zhan

Random walks on graphs can be slow. To speed them up, imagine that at each step instead of choosing the neighbor at random, there is a small probability $\varepsilon>0$ that we can choose it. We show that in this case, at least for graphs…

Probability · Mathematics 2026-05-19 Boris Bukh , Quentin Dubroff

We present a nonparametric prior over reversible Markov chains. We use completely random measures, specifically gamma processes, to construct a countably infinite graph with weighted edges. By enforcing symmetry to make the edges undirected…

Machine Learning · Statistics 2014-03-18 Konstantina Palla , David A. Knowles , Zoubin Ghahramani
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