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Population structure affects the outcome of natural selection. Static population structures can be described by graphs, where individuals occupy the nodes, and interactions occur along the edges. General conditions for evolutionary success…

Populations and Evolution · Quantitative Biology 2020-01-08 Benjamin Allen , Gabor Lippner , Martin A. Nowak

We study the intersection of a random geometric graph with an Erd\H{o}s-R\'enyi graph. Specifically, we generate the random geometric graph $G(n, r)$ by choosing $n$ points uniformly at random from $D=[0, 1]^2$ and joining any two points…

Combinatorics · Mathematics 2024-11-08 Patrick Bennett , Alan Frieze , Wesley Pegden

We investigate the higher-order connectivity of scale-free networks using algebraic topology. We model scale-free networks as preferential attachment graphs, and we study the algebraic-topological properties of their clique complexes. We…

Algebraic Topology · Mathematics 2025-02-25 Chunyin Siu

An emerging way of tackling the dimensionality issues arising in the modeling of a multivariate process is to assume that the inherent data structure can be captured by a graph. Nevertheless, though state-of-the-art graph-based methods have…

Machine Learning · Statistics 2016-07-13 Andreas Loukas , Nathanael Perraudin

Dynamic graphs refer to graphs whose structure dynamically changes over time. Despite the benefits of learning vertex representations (i.e., embeddings) for dynamic graphs, existing works merely view a dynamic graph as a sequence of changes…

Machine Learning · Computer Science 2023-11-02 Yu Yang , Hongzhi Yin , Jiannong Cao , Tong Chen , Quoc Viet Hung Nguyen , Xiaofang Zhou , Lei Chen

Random directed graphs $D(n,p)$ undergo a phase transition around the point $p = 1/n$, and the width of the transition window has been known since the works of Luczak and Seierstad. They have established that as $n \to \infty$ when $p = (1…

We study the Hamiltonicity of the following model of a random graph. Suppose that we partition [n] into V_1,V_2,...,V_k and add edge {x,y} to our graph with probability p if there exists i such that x,y\in V_i. Otherwise, we add the edge…

Combinatorics · Mathematics 2019-10-29 Michael Anastos , Alan Frieze , Pu Gao

We study the graph alignment problem over two independent Erd\H{o}s-R\'enyi graphs on $n$ vertices, with edge density $p$ falling into two regimes separated by the critical window around $p_c=\sqrt{\log n/n}$. Our result reveals an…

Probability · Mathematics 2025-03-27 Hang Du , Shuyang Gong , Rundong Huang

We consider two independent Erd\H{o}s-R\'enyi random graphs, with possibly different parameters, and study two isomorphism problems, a graph embedding problem and a common subgraph problem. Under certain conditions on the graph parameters…

Combinatorics · Mathematics 2025-06-25 Dimitris Diamantidis , Takis Konstantopoulos , Linglong Yuan

The topology of social networks can be understood as being inherently dynamic, with edges having a distinct position in time. Most characterizations of dynamic networks discretize time by converting temporal information into a sequence of…

Data Analysis, Statistics and Probability · Physics 2012-12-03 Aaron Clauset , Nathan Eagle

We consider an evolving network of a fixed number of nodes. The allocation of edges is a dynamical stochastic process inspired by biological reproduction dynamics, namely by deleting and duplicating existing nodes and their edges. The…

Statistical Mechanics · Physics 2007-09-14 Henrik Jeldtot Jensen

Various kinds of spread of influence occur in real world social and virtual networks. These phenomena are formulated by activation processes and irreversible dynamic monopolies in combinatorial graphs representing the topology of the…

Discrete Mathematics · Computer Science 2024-03-05 Manouchehr Zaker

We prove a sufficient condition for a finite clique complex to collapse to a $k$-dimensional complex, and use this to exhibit thresholds for $(k+1)$-collapsibility in a sparse random clique complex. In particular, if every strongly…

Combinatorics · Mathematics 2019-03-13 Greg Malen

Finding a Maximum Clique is a classic property test from graph theory; find any one of the largest complete subgraphs in an Erd\"os-R\'enyi G(N, p) random graph. We use Maximum Clique to explore the structure of the problem as a function of…

Disordered Systems and Neural Networks · Physics 2023-05-26 Raffaele Marino , Scott Kirkpatrick

In this work, we investigate the temporal evolution of the degree of a given vertex in a network by mapping the dynamics into a random walk problem in degree space. We analyze when the degree approximates a pre-established value through a…

Statistical Mechanics · Physics 2022-04-12 F. Ampuero , M. O. Hase

We study the expected topological properties of Cech and Vietoris-Rips complexes built on i.i.d. random points in R^d. We find higher dimensional analogues of known results for connectivity and component counts for random geometric graphs.…

Probability · Mathematics 2011-05-05 Matthew Kahle

Majority dynamics on the binomial Erd\H{o}s-R\'enyi graph $\mathsf{G}(n,p)$ with $p=\lambda/\sqrt{n}$ is studied. In this process, each vertex has a state in $\{0,1\}$ and at each round, every vertex adopts the state of the majority of its…

Data Structures and Algorithms · Computer Science 2022-10-14 Ran Tamir

We introduce a new class of latent process models for dynamic relational network data with the goal of detecting time-dependent structure. Network data are often observed over time, and static network models for such data may fail to…

Methodology · Statistics 2013-11-15 Lucy F. Robinson , Carey E. Priebe

We study the problem of approximating the number of $k$-cliques in a graph when given query access to the graph. We consider the standard query model for general graphs via (1) degree queries, (2) neighbor queries and (3) pair queries. Let…

Data Structures and Algorithms · Computer Science 2018-03-14 Talya Eden , Dana Ron , C. Seshadhri

We introduce perhaps the simplest models of graph evolution with choice that demonstrate discontinuous percolation transitions and can be analyzed via mathematical evolution equations. These models are local, in the sense that at each step…

Disordered Systems and Neural Networks · Physics 2011-03-31 Raissa M. D'Souza , Michael Mitzenmacher