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The biharmonic distance is a fundamental metric on graphs that measures the dissimilarity between two nodes, capturing both local and global structures. It has found applications across various fields, including network centrality, graph…

Social and Information Networks · Computer Science 2026-01-16 Dehong Zheng , Zhongzhi Zhang

We analyze complexity in spatial network ensembles through the lens of graph entropy. Mathematically, we model a spatial network as a soft random geometric graph, i.e., a graph with two sources of randomness, namely nodes located randomly…

Physics and Society · Physics 2018-05-02 Justin P. Coon , Carl P. Dettmann , Orestis Georgiou

Several interesting approaches have been reported in the literature on complex networks, random walks, and hierarchy of graphs. While many of these works perform random walks on stable, fixed networks, in the present work we address the…

Social and Information Networks · Computer Science 2024-03-12 Alexandre Benatti , Luciano da F. Costa

We apply the theory of unimodular random rooted graphs to study the metric geometry of large, finite, bounded degree graphs whose diameter is proportional to their volume. We prove that for a positive proportion of the vertices of such a…

Metric Geometry · Mathematics 2020-12-02 Itai Benjamini , Tom Hutchcroft

This work addresses a modification of the random geometric graph (RGG) model by considering a set of points uniformly and independently distributed on the surface of a $(d-1)$-sphere with radius $r$ in a $d-$dimensional Euclidean space,…

Physics and Society · Physics 2018-10-03 Alfonso Allen-Perkins

A generalization of the random geometric graph (RGG) model is proposed by considering a set of points uniformly and independently distributed on a rectangle of unit area instead of on a unit square [0,1]^2. The topological properties of the…

Physics and Society · Physics 2015-05-20 Ernesto Estrada , Matthew Sheerin

Many real world graphs have edges correlated to the distance between them, but, in an inhomogeneous manner. While the Chung-Lu model and the geometric random graph models both are elegant in their simplicity, they are insufficient to…

Combinatorics · Mathematics 2025-03-04 Susama Agarwala , Franklin Kenter

We consider the following dynamic problem: given a fixed (small) template graph with colored vertices C and a large graph with colored vertices G (whose colors can be changed dynamically), how many mappings m are there from the vertices of…

Data Structures and Algorithms · Computer Science 2021-11-02 Eryk Kopczyński , Dorota Celińska-Kopczyńska

Let $X_1,X_2,...$ be an infinite sequence of i.i.d. random vectors distributed exponentially with parameter $\lam .$ For each $y$ and $n\geq 1,$ form a graph $G_n(y)$ with vertex set $V_n = \{X_1,...,X_n\},$ two vertices are connected if…

Probability · Mathematics 2007-05-23 Bhupendra Gupta

We include complex connectivity structures and heterogeneity in models of multilayer networks or multilayer hypergraphs growing by preferential attachment. We consider the most generic connectivity structure, where the probability of…

Disordered Systems and Neural Networks · Physics 2025-05-26 Francesco Di Lauro , Luca Ferretti

Inspired by Pythagoras's belief that numbers are the absolute reality, we obtain some demonstrational results about topological properties of integer networks, in which the vertices represent integers and two vertices are neighbors if and…

Statistical Mechanics · Physics 2007-05-23 Tao Zhou , Bing-Hong Wang , P. -M. Hui , K. -P. Chan

Despite the recently exhibited importance of higher-order interactions for various processes, few flexible (null) models are available. In particular, most studies on hypergraphs focus on a small set of theoretical models. Here, we…

Statistical Mechanics · Physics 2022-12-28 Marc Barthelemy

Let $G$ be a large (simple, unlabeled) dense graph on $n$ vertices. Suppose that we only know, or can estimate, the empirical distribution of the number of subgraphs $F$ that each vertex in $G$ participates in, for some fixed small graph…

Information Theory · Computer Science 2023-08-08 Shahar Stein Ioushua , Ofer Shayevitz

Even though power-law or close-to-power-law degree distributions are ubiquitously observed in a great variety of large real networks, the mathematically satisfactory treatment of random power-law graphs satisfying basic statistical…

Probability · Mathematics 2023-11-09 Pim van der Hoorn , Gabor Lippner , Dmitri Krioukov

We delve into the statistical properties of regions within complex networks that are distant from vertices with high centralities, such as hubs or highly connected clusters. These remote regions play a pivotal role in shaping the asymptotic…

Physics and Society · Physics 2023-10-23 J. G. Oliveira , S. N. Dorogovtsev , J. F. F. Mendes

The average distance from a node to all other nodes in a graph, or from a query point in a metric space to a set of points, is a fundamental quantity in data analysis. The inverse of the average distance, known as the (classic) closeness…

Social and Information Networks · Computer Science 2015-06-29 Shiri Chechik , Edith Cohen , Haim Kaplan

Network geometry is currently a topic of growing scientific interest as it opens the possibility to explore and interpret the interplay between structure and dynamics of complex networks using geometrical arguments. However the field is…

Disordered Systems and Neural Networks · Physics 2019-08-21 Ivan Kryven , Robert M. Ziff , Ginestra Bianconi

Let $G=(V,E)$ be a finite, connected graph. We consider a greedy selection of vertices: given a list of vertices $x_1, \dots, x_k$, take $x_{k+1}$ to be any vertex maximizing the sum of distances to the existing vertices and iterate: we…

Combinatorics · Mathematics 2022-05-06 Stefan Steinerberger

Gromov hyperbolicity is an interesting geometric property, and so it is natural to study it in the context of geometric graphs. It measures the tree-likeness of a graph from a metric viewpoint. In particular, we are interested in…

Combinatorics · Mathematics 2020-04-07 R. Reyes , J. M. Rodriguez , J. M. Sigarreta , M. Villeta

Hypergraphs, graph generalizations where edges are conglomerates of $r$ nodes called hyperedges of rank $r\geq 2$, are excellent models to study systems with interactions that are beyond the pairwise level. For hypergraphs, the node degree…

Statistical Mechanics · Physics 2013-07-11 Eduardo López
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