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We equip the edges of a deterministic graph $H$ with independent but not necessarily identically distributed weights and study a generalized version of matchings (i.e. a set of vertex disjoint edges) in $H$ satisfying the property that…

Probability · Mathematics 2021-08-18 Ghurumuruhan Ganesan

Graph homologies are powerful tools to compute the rational homotopy group of the space of long embeddings. Two graph homologies have been invented from two approaches to study the space of long embeddings: the hairy graph homology from…

Geometric Topology · Mathematics 2023-10-18 Leo Yoshioka

We consider a variant of so called power-law random graph. A sequence of expected degrees corresponds to a power-law degree distribution with finite mean and infinite variance. In previous works the asymptotic picture with number of nodes…

Probability · Mathematics 2007-12-12 Hannu Reittu , Ilkka Norros

Force-directed layouts belong to a popular class of methods used to position nodes in a node-link diagram. However, they typically lack direct consideration of global structures, which can result in visual clutter and the overlap of…

Human-Computer Interaction · Computer Science 2022-08-16 Bhavana Doppalapudi , Bei Wang , Paul Rosen

For each commutative, graded algebra with finite dimension in each degree, we construct a graded cohomology theory for graphs whose graded Euler characteristic is the chromatic polynomial of the graph. This extends our previous work which…

Quantum Algebra · Mathematics 2007-05-23 Laure Helme-Guizon , Yongwu Rong

We associate all small subgraph counting problems with a systematic graph encoding/representation system which makes a coherent use of graphlet structures. The system can serve as a unified foundation for studying and connecting many…

Discrete Mathematics · Computer Science 2021-03-22 Dimitris Floros , Nikos Pitsianis , Xiaobai Sun

We view hyper-graphs as incidence graphs, i.e. bipartite graphs with a set of nodes representing vertices and a set of nodes representing hyper-edges, with two nodes being adjacent if the corresponding vertex belongs to the corresponding…

Logic in Computer Science · Computer Science 2015-05-08 Nans Lefebvre

Many inequality relations between real vector quantities can be succinctly expressed as "weak (sub)majorization" relations. We explain these ideas and apply them in several areas: angles between subspaces, Ritz values, and graph Laplacian…

Numerical Analysis · Mathematics 2013-03-26 A. V. Knyazev , M. E. Argentati

Unigraphs are graphs uniquely determined by their own degree sequence up to isomorphism. There are many subclasses of unigraphs such as threshold graphs, split matrogenic graphs, matroidal graphs, and matrogenic graphs. Unigraphs and these…

Data Structures and Algorithms · Computer Science 2019-04-23 Takashi Horiyama , Jun Kawahara , Shin-ichi Minato , Yu Nakahata

In an increasingly interconnected world, understanding and summarizing the structure of these networks becomes increasingly relevant. However, this task is nontrivial; proposed summary statistics are as diverse as the networks they…

Statistics Theory · Mathematics 2020-04-15 Lee M. Gunderson , Gecia Bravo-Hermsdorff

We introduce new methods for understanding the topology of $\Hom$ complexes (spaces of homomorphisms between two graphs), mostly in the context of group actions on graphs and posets. We view $\Hom(T,-)$ and $\Hom(-,G)$ as functors from…

Combinatorics · Mathematics 2015-03-13 Anton Dochtermann , Carsten Schultz

Arone and the second author showed that when the dimensions are in the stable range, the rational homology and homotopy of the high dimensional anologues of spaces of long knots can be calculated as the homology of a direct sum of finite…

Algebraic Topology · Mathematics 2017-09-28 Paul Arnaud Songhafouo Tsopméné , Victor Turchin

We introduce submodular hypergraphs, a family of hypergraphs that have different submodular weights associated with different cuts of hyperedges. Submodular hypergraphs arise in clustering applications in which higher-order structures carry…

Machine Learning · Computer Science 2018-10-12 Pan Li , Olgica Milenkovic

Hypergraphs naturally represent group interactions, which are omnipresent in many domains: collaborations of researchers, co-purchases of items, joint interactions of proteins, to name a few. In this work, we propose tools for answering the…

Social and Information Networks · Computer Science 2020-07-21 Geon Lee , Jihoon Ko , Kijung Shin

This paper is mainly a semi-tutorial introduction to elementary algebraic topology and its applications to Ising-type models of statistical physics, using graphical models of linear and group codes. It contains new material on systematic…

Information Theory · Computer Science 2018-12-20 G. David Forney

Hyperuniformity, the suppression of density fluctuations at large length scales, is observed across a wide variety of domains, from cosmology to condensed matter and biological systems. Although the standard definition of hyperuniformity…

Statistical Mechanics · Physics 2024-05-07 Marco Salvalaglio , Dominic J. Skinner , Jörn Dunkel , Axel Voigt

Subgraph densities have been defined, and served as basic tools, both in the case of graphons (limits of dense graph sequences) and graphings (limits of bounded-degree graph sequences). While limit objects have been described for the…

Combinatorics · Mathematics 2021-05-11 Dávid Kunszenti-Kovács , László Lovász , Balázs Szegedy

In this paper we derive results concerning the connected components and the diameter of random graphs with an arbitrary i.i.d. degree sequence. We study these properties primarily, but not exclusively, when the tail of the degree…

Probability · Mathematics 2007-05-23 Remco van der Hofstad , Gerard Hooghiemstra , Dmitri Znamenski

We use random matrix theory to study the spectrum of random geometric graphs, a fundamental model of spatial networks. Considering ensembles of random geometric graphs we look at short range correlations in the level spacings of the…

Physics and Society · Physics 2017-06-08 Carl P. Dettmann , Orestis Georgiou , Georgie Knight

We present a new algorithm for computing the first discrete homology group of a graph. By testing the algorithm on different data sets of random graphs, we find that it significantly outperforms other known algorithms.

Computational Geometry · Computer Science 2025-12-17 Jacob Ender , Chris Kapulkin