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We quantify the dynamical implications of the small-world phenomenon. We consider the generic synchronization of oscillator networks of arbitrary topology, and link the linear stability of the synchronous state to an algebraic condition of…

Chaotic Dynamics · Physics 2009-11-07 Mauricio Barahona , Louis M. Pecora

We study Laplacians on graphs and networks via regular Dirichlet forms. We give a sufficient geometric condition for essential selfadjointness and explicitly determine the generators of the associated semigroups on all $\ell^p$, $1\leq p <…

Functional Analysis · Mathematics 2011-04-14 Matthias Keller , Daniel Lenz

Spectral approaches of network analysis heavily rely upon the eigendecomposition of the graph Laplacian. For instance, in graph signal processing, the Laplacian eigendecomposition is used to define the graph Fourier transform and then…

Machine Learning · Computer Science 2017-08-21 Dimitri Van De Ville , Robin Demesmaeker , Maria Giulia Preti

A class of graphs is bridge-addable if given a graph $G$ in the class, any graph obtained by adding an edge between two connected components of $G$ is also in the class. We prove a conjecture of McDiarmid, Steger, and Welsh, that says that…

Combinatorics · Mathematics 2023-06-23 Guillaume Chapuy , Guillem Perarnau

This introduction to graphs and graph algebras provides the optimal bound for the number of all paths of length $k$ in a graph with $N\geq k$ edges and no loops. Our proof relies on a construction of a number of terminating algorithms that…

Rings and Algebras · Mathematics 2019-12-12 Piotr M. Hajac , Mariusz Tobolski

Real-world optimization problems are generally not just black-box problems, but also involve mixed types of inputs in which discrete and continuous variables coexist. Such mixed-space optimization possesses the primary challenge of modeling…

Machine Learning · Computer Science 2022-02-09 Jaeyeon Ahn , Taehyeon Kim , Seyoung Yun

For a given graph $\mathcal{G}$ of order $n$ with $m$ edges, and a real symmetric matrix associated to the graph, $M\left(\mathcal{G}\right)\in\mathbb{R}^{n\times n}$, the interlacing graph reduction problem is to find a graph…

Spectral Theory · Mathematics 2020-08-11 Noam Leiter , Daniel Zelazo

For distinct vertices $u$ and $v$ in a graph $G$, the {\em connectivity} between $u$ and $v$, denoted $\kappa_G(u,v)$, is the maximum number of internally disjoint $u$--$v$ paths in $G$. The {\em average connectivity} of $G$, denoted…

Combinatorics · Mathematics 2019-07-18 Rocio M. Casablanca , Peter Dankelmann , Wayne Goddard , Ortrud R. Oellermann , Lucas Mol

We study the algebraic connectivity for several classes of random semi-regular graphs. For large random semi-regular bipartite graphs, we explicitly compute both their algebraic connectivity and as well as the full spectrum distribution.…

Combinatorics · Mathematics 2022-01-07 Theodore Kolokolnikov

The $k$-token graph $F_k(G)$ of a graph $G$ is the graph whose vertices are the $k$-subsets of vertices from $G$, two of which being adjacent whenever their symmetric difference is a pair of adjacent vertices in $G$. It is a known result…

Combinatorics · Mathematics 2023-09-14 Mónica. A. Reyes , Cristina Dalfó , Miquel Àngel Fiol , Arnau Messegué

For a given digraph $D$ and distinct $u,v \in V(D)$, we denote by $\lambda_D(u,v)$ the local arc-connectivity from $u$ to $v$. Further, we define the total arc-connectivity $tac(D)$ of $D$ to be $\sum_{\{u,v\}\subseteq…

Combinatorics · Mathematics 2023-08-31 Florian Hörsch

A basic fact in spectral graph theory is that the number of connected components in an undirected graph is equal to the multiplicity of the eigenvalue zero in the Laplacian matrix of the graph. In particular, the graph is disconnected if…

Metric Geometry · Mathematics 2014-11-24 James R. Lee , Shayan Oveis Gharan , Luca Trevisan

Graph coarsening is a widely used dimensionality reduction technique for approaching large-scale graph machine learning problems. Given a large graph, graph coarsening aims to learn a smaller-tractable graph while preserving the properties…

Machine Learning · Statistics 2022-10-04 Manoj Kumar , Anurag Sharma , Sandeep Kumar

We consider the problem of decentralized composite optimization over a symmetric connected graph, in which each node holds its own agent-specific private convex functions, and communications are only allowed between nodes with direct links.…

Optimization and Control · Mathematics 2018-09-06 Bin Wang , Jun Fang , Huiping Duan , Hongbin Li

We aim to learn a sparse and connected graph from sparse data, where the number of observations K can be substantially smaller than the signal dimension N for signals x in R^N, and the underlying distribution is unknown. In this severely…

Signal Processing · Electrical Eng. & Systems 2026-04-30 Bahar Oveisgharan , Gene Cheung , Andrew Eckford

The Laplacian eigenvalues of a network play an important role in the analysis of many structural and dynamical network problems. In this paper, we study the relationship between the eigenvalue spectrum of the normalized Laplacian matrix and…

Social and Information Networks · Computer Science 2013-10-21 Zhengwei Wu , Victor M. Preciado

Connectivity is a fundamental property of quantum graphs, previously studied in the operator system model for matrix quantum graphs and via graph homomorphisms in the quantum adjacency matrix model. In this paper, we develop an algebraic…

Operator Algebras · Mathematics 2025-05-29 Kristin Courtney , Priyanga Ganesan , Mateusz Wasilewski

Consider a semigraph $G=(V,\,E)$; in this paper, we study the eigenvalues of the Laplacian matrix of $G$. We show that the Laplacian of $G$ is positive semi-definite, and $G$ is connected if and only if $\lambda_2 >0.$ Along the similar…

Combinatorics · Mathematics 2023-07-10 Pralhad M. Shinde

The graph partition problem is the problem of partitioning the vertex set of a graph into a fixed number of sets of given sizes such that the sum of weights of edges joining different sets is optimized. In this paper we simplify a known…

Optimization and Control · Mathematics 2015-11-25 Edwin R. van Dam , Renata Sotirov

Simultaneous localization and mapping (SLAM) is a critical capability in autonomous navigation, but memory and computational limits make long-term application of common SLAM techniques impractical; a robot must be able to determine what…

Robotics · Computer Science 2024-08-05 Kevin Doherty , Alan Papalia , Yewei Huang , David Rosen , Brendan Englot , John Leonard
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