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Analyzing social graphs with limited data access is challenging for third-party researchers. To address this challenge, a number of algorithms that estimate structural properties via a random walk have been developed. However, most existing…

Social and Information Networks · Computer Science 2022-01-21 Kazuki Nakajima , Kazuyuki Shudo

A theorem of Hoffman gives an upper bound on the independence ratio of regular graphs in terms of the minimum $\lambda_{\min}$ of the spectrum of the adjacency matrix. To complement this result we use random eigenvectors to gain lower…

Probability · Mathematics 2016-08-11 Viktor Harangi , Bálint Virág

Parametric resampling schemes have been recently introduced in complex network analysis with the aim of assessing the statistical significance of graph clustering and the robustness of community partitions. We propose here a method to…

Physics and Society · Physics 2014-02-25 Fabrizio De Vico Fallani , Vincenzo Nicosia , Vito Latora , Mario Chavez

In this paper we investigate the reachability and observability properties of a network system, running a Laplacian based average consensus algorithm, when the communication graph is a path or a cycle. More in detail, we provide necessary…

Optimization and Control · Mathematics 2015-03-19 Gianfranco Parlangeli , Giuseppe Notarstefano

Binomial random intersection graphs can be used as parsimonious statistical models of large and sparse networks, with one parameter for the average degree and another for transitivity, the tendency of neighbours of a node to be connected.…

Social and Information Networks · Computer Science 2018-06-26 Joona Karjalainen , Lasse Leskelä

We initiate the study of property testing in arbitrary planar graphs. We prove that bipartiteness can be tested in constant time, improving on the previous bound of $\tilde{O}(\sqrt{n})$ for graphs on $n$ vertices. The constant-time…

Data Structures and Algorithms · Computer Science 2018-12-27 Artur Czumaj , Morteza Monemizadeh , Krzysztof Onak , Christian Sohler

We give upper and lower bounds on the spectral radius of a graph in terms of the number of walks. We generalize a number of known results.

Combinatorics · Mathematics 2007-05-23 Vladimir Nikiforov

We consider Reinforced Random Walks where transition probabilities are a function of the proportion of times the walk has traversed an edge. We give conditions for recurrence or transience. A phase transition is observed, similar to…

Probability · Mathematics 2009-07-15 Olivier Raimond , Bruno Schapira

We consider a random object that is associated with both random walks and random media, specifically, the superposition of a configuration of subcritical Bernoulli percolation on an infinite connected graph and the trace of the simple…

Probability · Mathematics 2019-09-10 Kazuki Okamura

Fractional revival occurs between two vertices in a graph if a continuous-time quantum walk unitarily maps the characteristic vector of one vertex to a superposition of the characteristic vectors of the two vertices. This phenomenon is…

Combinatorics · Mathematics 2019-07-11 Ada Chan , Gabriel Coutinho , Christino Tamon , Luc Vinet , Hanmeng Zhan

The number of homomorphisms from a finite graph $F$ to the complete graph $K_n$ is the evaluation of the chromatic polynomial of $F$ at $n$. Suitably scaled, this is the Tutte polynomial evaluation $T(F;1-n,0)$ and an invariant of the cycle…

Combinatorics · Mathematics 2016-02-25 Andrew Goodall , Guus Regts , Lluis Vena

In case of sparse graphs, relation between the real eigenvalues of the non-backtracking matrix and those of the non-backtracking transition probability matrix is considered with respect to vertex clustering. For this purpose, the random…

Combinatorics · Mathematics 2026-05-26 Marianna Bolla

A mixed graph is cospectral to its converse, with respect to the usual adjacency matrices. Hence, it is easy to see that a mixed graph whose eigenvalues occur uniquely, up to isomorphism, must be isomorphic to its converse. It is therefore…

Combinatorics · Mathematics 2021-11-08 Pepijn Wissing

P-time event graphs are discrete event systems able to model cyclic production systems where tasks need to be performed within given time windows. Consistency is the property of admitting an infinite execution of such tasks that does not…

Logic in Computer Science · Computer Science 2026-02-10 Davide Zorzenon , Jörg Raisch

Classical results in sparse recovery guarantee the exact reconstruction of $s$-sparse signals under assumptions on the dictionary that are either too strong or NP-hard to check. Moreover, such results may be pessimistic in practice since…

Information Theory · Computer Science 2019-04-04 Mengnan Zhao , M. Devrim Kaba , René Vidal , Daniel P. Robinson , Enrique Mallada

We introduce a very general model of an inhomogenous random graph with independence between the edges, which scales so that the number of edges is linear in the number of vertices. This scaling corresponds to the p=c/n scaling for G(n,p)…

Probability · Mathematics 2011-11-10 Bela Bollobas , Svante Janson , Oliver Riordan

Due to wide applications in diverse fields, random walks subject to stochastic resetting have attracted considerable attention in the last decade. In this paper, we study discrete-time random walks on complex network with multiple resetting…

Statistical Mechanics · Physics 2021-10-01 Shuang Wang , Hanshuang Chen , Feng Huang

For polynomials and rational maps of fixed degree over a finite field, we bound both the average number of connected components of their functional graphs as well as the average number of periodic points of their associated dynamical…

Dynamical Systems · Mathematics 2014-07-01 Ryan Flynn , Derek Garton

Intransitivity is a property of connected, oriented graphs representing species interactions that may drive their coexistence even in the presence of competition, the standard example being the three species Rock-Paper-Scissors game. We…

Populations and Evolution · Quantitative Biology 2013-02-19 Alessandra F. Lütz , Sebastián Risau-Gusman , Jeferson J. Arenzon

Many signals evolve in time as a stochastic process, randomly switching between states over discretely sampled time points. Here we make an explicit link between the underlying stochastic process of a signal that can take on a bounded…

Machine Learning · Statistics 2026-05-11 Stefan Klus , Jason J. Bramburger