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Related papers: Sparse graphs of high gonality

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In recent years, discrete spaces such as graphs attract much attention as models for physical spacetime or as models for testing the spirit of non-commutative geometry. In this work, we construct the differential algebras for graphs by…

q-alg · Mathematics 2016-09-08 Sunggoo Cho , Kwang Sung Park

In 2013, Chan classified all metric hyperelliptic graphs, proving that divisorial gonality and geometric gonality are equivalent in the hyperelliptic case. We show that such a classification extends to combinatorial graphs of divisorial…

Combinatorics · Mathematics 2020-03-06 Ivan Aidun , Frances Dean , Ralph Morrison , Teresa Yu , Julie Yuan

Highly connected and yet sparse graphs (such as expanders or graphs of high treewidth) are fundamental, widely applicable and extensively studied combinatorial objects. We initiate the study of such highly connected graphs that are, in…

Computational Geometry · Computer Science 2013-06-17 Prosenjit Bose , Vida Dujmovic , Pat Morin , Michiel Smid

Graphons are limit objects of sequences of graphs and are used to analyze the behavior of large graphs. Recently, graphon signal processing has been developed to study signal processing on large graphs. A major limitation of this approach…

Signal Processing · Electrical Eng. & Systems 2024-03-26 Feng Ji , Xingchao Jian , Wee Peng Tay

Let R be any subring of the reals. We present a generalization of linear systems on graphs where divisors are R-valued functions on the set of vertices and graph edges are permitted to have nonegative weights in R. Using this…

Algebraic Geometry · Mathematics 2017-11-13 Rodney James , Rick Miranda

The gonality of a graph measures how difficult it is to move chips around the entirety of a graph according to certain chip-firing rules without introducing debt. In this paper we study the gonality of circulant graphs, a class of…

We study harmonic morphisms of graphs as a natural discrete analogue of holomorphic maps between Riemann surfaces. We formulate a graph-theoretic analogue of the classical Riemann-Hurwitz formula, study the functorial maps on Jacobians and…

Combinatorics · Mathematics 2007-07-18 Matthew Baker , Serguei Norine

We address a question posed by Fessler-Jensen-Kelsey-Owen regarding graphs whose second gonality is greater than the first by exactly 1. We answer the question affirmatively under a stronger condition, thereby characterising the entire…

Combinatorics · Mathematics 2025-11-25 Šimun Dropuljić , Yoav Len

The Subgraph Isomorphism problem asks, given a host graph G on n vertices and a pattern graph P on k vertices, whether G contains a subgraph isomorphic to P. The restriction of this problem to planar graphs has often been considered. After…

Discrete Mathematics · Computer Science 2015-03-19 Paul Bonsma

A graph is "$H$-free" if it has no induced subgraph isomorphic to $H$. A conjecture of Conlon, Fox and Sudakov states that for every graph $H$, there exists $s>0$ such that in every $H$-free graph with $n>1$ vertices, either some vertex has…

Combinatorics · Mathematics 2020-12-08 Maria Chudnovsky , Jacob Fox , Alex Scott , Paul Seymour , Sophie Spirkl

In this survey, we explore recent literature on finding the cores of higher graphs using geometric and topological means. We study graphs, hypergraphs, and simplicial complexes, all of which are models of higher graphs. We study the notion…

History and Overview · Mathematics 2025-06-30 Inés García-Redondo , Claudia Landi , Sarah Percival , Anda Skeja , Bei Wang , Ling Zhou

We study the interplay between the classical theory of linear series on curves, and the recent theory of linear series on graphs. We prove that every d-gonal (weighted) graph of Hurwitz type is the dual graph of a d-gonal curve. Conversely…

Algebraic Geometry · Mathematics 2013-07-23 Lucia Caporaso

We define a new graph invariant called the scramble number. We show that the scramble number of a graph is a lower bound for the gonality and an upper bound for the treewidth. Unlike the treewidth, the scramble number is not minor monotone,…

Combinatorics · Mathematics 2021-11-08 Michael Harp , Elijah Jackson , David Jensen , Noah Speeter

In this manuscript a unified framework for conducting inference on complex aggregated data in high dimensional settings is proposed. The data are assumed to be a collection of multiple non-Gaussian realizations with underlying undirected…

Applications · Statistics 2013-10-14 Fang Han , Han Liu , Brian Caffo

Graphs are naturally sparse objects that are used to study many problems involving networks, for example, distributed learning and graph signal processing. In some cases, the graph is not given, but must be learned from the problem and…

Machine Learning · Statistics 2017-08-31 Martin Sundin , Arun Venkitaraman , Magnus Jansson , Saikat Chatterjee

We consider the following two algorithmic problems: given a graph $G$ and a subgraph $H\subseteq G$, decide whether $H$ is an isometric or a geodesically convex subgraph of $G$. It is relatively easy to see that the problems can be solved…

Data Structures and Algorithms · Computer Science 2026-04-14 Sergio Cabello

These notes concern aspects of various graphs whose vertex set is a group $G$ and whose edges reflect group structure in some way (so that they are invariant under the action of the automorphism group of $G$). The graphs I will discuss are…

Group Theory · Mathematics 2021-03-29 Peter J. Cameron

We propose a statistical model for graphs with a core-periphery structure. To do this we define a precise notion of what it means for a graph to have this structure, based on the sparsity properties of the subgraphs of core and periphery…

Methodology · Statistics 2019-10-23 Cian Naik , François Caron , Judith Rousseau

We introduce a new variant of the coarse Baum-Connes conjecture designed to tackle coarsely disconnected metric spaces called the boundary coarse Baum-Connes conjecture. We prove this conjecture for many coarsely disconnected spaces that…

K-Theory and Homology · Mathematics 2014-07-23 Martin Finn-Sell , Nick Wright

Graph signal processing (GSP) provides a powerful framework for analyzing signals arising in a variety of domains. In many applications of GSP, multiple network structures are available, each of which captures different aspects of the same…

Machine Learning · Statistics 2021-11-03 Michael Weylandt , George Michailidis , T. Mitchell Roddenberry