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Vertex bisection is a graph partitioning problem in which the aim is to find a partition into two equal parts that minimizes the number of vertices in one partition set that have a neighbor in the other set. We are interested in giving…

Data Structures and Algorithms · Computer Science 2022-11-08 Josep Díaz , Öznur Yaşar Diner , Maria Serna , Oriol Serra

Twisted $K$-homology corresponds to $D$-branes in string theory. In this paper we compare two different models of geometric twisted $K$-homology and get their equivalence. Moreover, we give another description of geometric twisted…

K-Theory and Homology · Mathematics 2014-11-17 Bei Liu

We continue the study of the properties of graphs in which the ball of radius $r$ around each vertex induces a graph isomorphic to the ball of radius $r$ in some fixed vertex-transitive graph $F$, for various choices of $F$ and $r$. This is…

Combinatorics · Mathematics 2020-11-25 Itai Benjamini , David Ellis

Conventional X-ray methods use incoming plane waves and result in discrete diffraction patterns when scattered at crystals. Here we find, by a systematic method, incoming waveforms which exhibit discrete diffraction patterns when scattered…

Optics · Physics 2015-06-16 Gero Friesecke , Richard D. James , Dominik Jüstel

Let the class A of graphs be bridge-addable; that is, whenever a graph G in A has vertices u and v in different components then the graph G+uv is in A. For a random graph sampled uniformly from the graphs in A on vertex set {1,..,n}, there…

Combinatorics · Mathematics 2020-06-04 Colin McDiarmid

Highly dynamic peer-to-peer networks are becoming very significant due to their wide range of applications. Although many structures were proposed to deploy peer-to-peer networks, hypercube structures could grasp the researchers' attention…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-05-06 Reem Abdel-Rahman Osman , Omar H. Karam

An r-cut of a k-uniform hypergraph H is a partition of the vertex set of H into r parts and the size of the cut is the number of edges which have a vertex in each part. A classical result of Edwards says that every m-edge graph has a 2-cut…

Combinatorics · Mathematics 2019-07-01 David Conlon , Jacob Fox , Matthew Kwan , Benny Sudakov

We consider random hyperbolic graphs in hyperbolic spaces of any dimension $d+1\geq 2$. We present a rescaling of model parameters that casts the random hyperbolic graph model of any dimension to a unified mathematical framework, leaving…

Physics and Society · Physics 2024-06-04 Gabriel Budel , Maksim Kitsak , Rodrigo Aldecoa , Konstantin Zuev , Dmitri Krioukov

This paper consists of two halves. In the first half of the paper, we consider real-valued functions $f$ whose domain is the vertex set of a graph $G$ and that are Lipschitz with respect to the graph distance. By placing a uniform…

Combinatorics · Mathematics 2017-05-30 Matthew Yancey

We study thresholds for the appearance of a 2-core in random hypergraphs that are a mixture of a constant number of random uniform hypergraphs each with a linear number of edges but with different edge sizes. For the case of two overlapping…

Data Structures and Algorithms · Computer Science 2012-04-11 Michael Rink

We study random graph models for directed acyclic graphs, an important class of networks that includes citation networks, food webs, and feed-forward neural networks among others. We propose two specific models, roughly analogous to the…

Physics and Society · Physics 2009-10-16 Brian Karrer , M. E. J. Newman

We provide precise asymptotic estimates for the number of several classes of labelled cubic planar graphs, and we analyze properties of such random graphs under the uniform distribution. This model was first analyzed by Bodirsky et al.…

Combinatorics · Mathematics 2019-07-26 Marc Noy , Clément Requilé , Juanjo Rué

Random tensor networks provide useful models that incorporate various important features of holographic duality. A tensor network is usually defined for a fixed graph geometry specified by the connection of tensors. In this paper, we…

High Energy Physics - Theory · Physics 2017-09-13 Xiao-Liang Qi , Zhao Yang , Yi-Zhuang You

The main paradigm of smoothed analysis on graphs suggests that for any large graph $G$ in a certain class of graphs, perturbing slightly the edges of $G$ at random (usually adding few random edges to $G$) typically results in a graph having…

Combinatorics · Mathematics 2015-08-13 Michael Krivelevich , Daniel Reichman , Wojciech Samotij

The aim of this paper is to endow the well-known family of hypercubic quantization hashing methods with theoretical guarantees. In hypercubic quantization, applying a suitable (random or learned) rotation after dimensionality reduction has…

Machine Learning · Computer Science 2018-02-13 Anne Morvan , Antoine Souloumiac , Krzysztof Choromanski , Cédric Gouy-Pailler , Jamal Atif

In recent decades, it has been emphasized that the evolving structure of networks may be shaped by interaction principles that yield sparse graphs with a vertex degree distribution exhibiting an algebraic tail, and other structural traits…

Statistical Mechanics · Physics 2025-07-01 Dario Borrelli

In this paper we focus on the problem of finding (small) subhypergraphs in a (large) hypergraph. We use this problem to illustrate that reducing hypergraph problems to graph problems by working with the 2-section is not always a reasonable…

A random intersection graph is constructed by independently assigning a subset of a given set of objects $W,$ to each vertex of the vertex set $V$ of a simple graph $G.$ There is an edge between two vertices of $V,$ iff their respective…

Probability · Mathematics 2008-09-09 Bhupendra Gupta

We revisit the classical question of the relationship between the diameter of a graph and its expansion properties. One direction is well understood: expander graphs exhibit essentially the lowest possible diameter. We focus on the reverse…

Combinatorics · Mathematics 2017-11-23 Michael Dinitz , Michael Schapira , Gal Shahaf

Graph embeddings, wherein the nodes of the graph are represented by points in a continuous space, are used in a broad range of Graph ML applications. The quality of such embeddings crucially depends on whether the geometry of the space…

Machine Learning · Statistics 2022-02-03 Francesco Di Giovanni , Giulia Luise , Michael Bronstein