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Finding graph indices which are unbiased to network size and density is of high importance both within a given field and across fields for enhancing comparability of modern network science studies. The degree variance is an important metric…

Social and Information Networks · Computer Science 2021-01-26 Keith M. Smith , Javier Escudero

Contrary to many recent models of growing networks, we present a model with fixed number of nodes and links, where it is introduced a dynamics favoring the formation of links between nodes with degree of connectivity as different as…

Statistical Mechanics · Physics 2007-05-23 M. Baiesi , S. S. Manna

We perform a massive evaluation of neural networks with architectures corresponding to random graphs of various types. We investigate various structural and numerical properties of the graphs in relation to neural network test accuracy. We…

Machine Learning · Computer Science 2020-12-03 Romuald A. Janik , Aleksandra Nowak

The "slope-number" of a graph $G$ is the minimum number of distinct edge slopes in a straight-line drawing of $G$ in the plane. We prove that for $\Delta\geq5$ and all large $n$, there is a $\Delta$-regular $n$-vertex graph with…

Combinatorics · Mathematics 2008-09-09 Vida Dujmovic' , Matthew Suderman , David R. Wood

We obtain closed form expressions for the expected conditional degree distribution and the joint degree distribution of the linear preferential attachment model for network growth in the steady state. We consider the multiple-destination…

Statistical Mechanics · Physics 2014-06-30 Babak Fotouhi , Michael G. Rabbat

In this paper, we study some important statistics of the random graph in the directed preferential attachment model introduced by B. Bollob\'as, C. Borgs, J. Chayes and O. Riordan. First, we find a new asymptotic formula for the expectation…

Probability · Mathematics 2014-08-12 E. A. Grechnikov

In this paper, we propose a simple rule that generates scale-free small-world networks with tunable assortative coefficient. These networks are constructed by two-stage adding process for each new node. The model can reproduce scale-free…

Physics and Society · Physics 2009-11-11 Qiang Guo , Tao Zhou , Jian-Guo Liu , Wen-Jie Bai , Bing-Hong Wang , Ming Zhao

Breaking of equivalence between the microcanonical ensemble and the canonical ensemble, describing a large system subject to hard and soft constraints, respectively, was recently shown to occur in large random graphs. Hard constraints must…

Probability · Mathematics 2017-06-06 Diego Garlaschelli , Frank den Hollander , Andrea Roccaverde

Network modeling based on ensemble averages tacitly assumes that the networks meant to be modeled are typical in the ensemble. Previous research on network eigenvalues, which govern a range of dynamical phenomena, has shown that this is…

Disordered Systems and Neural Networks · Physics 2011-11-29 Nicole Carlson , Dong-Hee Kim , Adilson E. Motter

Analysis of degree-degree dependencies in complex networks, and their impact on processes on networks requires null models, i.e. models that generate uncorrelated scale-free networks. Most models to date however show structural negative…

Physics and Society · Physics 2015-08-12 Pim van der Hoorn , Nelly Litvak

1. Basic constructions. 2. Equilibrium and nonequilibrium networks. 3. Equilibrium uncorrelated networks. 4. Nonequilibrium nongrowing scale-free nets. 5. Types of correlations. 6. When pair correlations are important. 7. When loops are…

Statistical Mechanics · Physics 2007-05-23 S. N. Dorogovtsev , J. F. F. Mendes , A. N. Samukhin

The evolution of random undirected graphs by the clustering attachment (CA) both without node and edge deletion and with uniform node or edge deletion is investigated. Theoretical results are obtained for the CA without node and edge…

Statistics Theory · Mathematics 2024-03-04 Natalia Markovich , Maksim Ryzhov , Marijus Vaičiulis

We describe a new method for the random sampling of connected networks with a specified degree sequence. We consider both the case of simple graphs and that of loopless multigraphs. The constraints of fixed degrees and of connectedness are…

Physics and Society · Physics 2020-12-03 Szabolcs Horvát , Carl D. Modes

We propose that negative degree correlation among nodes in a network of nonlinear oscillators, often detected in real world networks, is motivated by its positive effects on synchronizability. In so doing, we use a novel methodology to…

Disordered Systems and Neural Networks · Physics 2007-12-08 Mario di Bernardo , Franco Garofalo , Francesco Sorrentino

We investigate the number of maximal cliques, i.e., cliques that are not contained in any larger clique, in three network models: Erd\H{o}s-R\'enyi random graphs, inhomogeneous random graphs (also called Chung-Lu graphs), and geometric…

Combinatorics · Mathematics 2024-11-27 Thomas Bläsius , Maximillian Katzmann , Clara Stegehuis

We analyze the degree distribution's cut-off in finite size scale-free networks. We show that the cut-off behavior with the number of vertices $N$ is ruled by the topological constraints induced by the connectivity structure of the network.…

Disordered Systems and Neural Networks · Physics 2009-11-10 Marian Boguna , Romualdo Pastor-Satorras , Alessandro Vespignani

We investigate the impact of degree-degree correlations on the spectra of networks. Even though density distributions exhibit drastic changes depending on the (dis)assortative mixing and the network architecture, the short range…

Physics and Society · Physics 2015-02-06 Sarika Jalan , Alok Yadav

Let $F$ be a probability distribution with support on the non-negative integers. Four methods for generating a simple undirected graph with (approximate) degree distribution $F$ are described and compared. Two methods are based on the so…

Probability · Mathematics 2015-09-30 Tom Britton , Maria Deijfen , Anders Martin-Löf

Large real-life complex networks are often modeled by various random graph constructions and hundreds of further references therein. In many cases it is not at all clear how the modeling strength of differently generated random graph model…

Data Structures and Algorithms · Computer Science 2020-09-01 András Faragó , Rupei Xu

We describe the asymptotic behaviour of large degrees in random hyperbolic graphs, for all values of the curvature parameter $ \alpha$. We prove that, with high probability, the node degrees satisfy the following ordering property: the…

Probability · Mathematics 2025-03-27 Loïc Gassmann