{"title":"Approximating Densest Subgraph in Geometric Intersection Graphs","authors":"Sariel Har-Peled, Rahul Saladi","doi":"arxiv-2405.18337","DOIUrl":null,"url":null,"abstract":"$ \\newcommand{\\cardin}[1]{\\left| {#1} \\right|}%\n\\newcommand{\\Graph}{\\Mh{\\mathsf{G}}}% \\providecommand{\\G}{\\Graph}%\n\\renewcommand{\\G}{\\Graph}% \\providecommand{\\GA}{\\Mh{H}}%\n\\renewcommand{\\GA}{\\Mh{H}}% \\newcommand{\\VV}{\\Mh{\\mathsf{V}}}%\n\\newcommand{\\VX}[1]{\\VV\\pth{#1}}% \\providecommand{\\EE}{\\Mh{\\mathsf{E}}}%\n\\renewcommand{\\EE}{\\Mh{\\mathsf{E}}}% \\newcommand{\\Re}{\\mathbb{R}}\n\\newcommand{\\reals}{\\mathbb{R}} \\newcommand{\\SetX}{\\mathsf{X}}\n\\newcommand{\\rad}{r} \\newcommand{\\Mh}[1]{#1} \\newcommand{\\query}{q}\n\\newcommand{\\eps}{\\varepsilon} \\newcommand{\\VorX}[1]{\\mathcal{V} \\pth{#1}}\n\\newcommand{\\Polygon}{\\mathsf{P}} \\newcommand{\\IntRange}[1]{[ #1 ]}\n\\newcommand{\\Space}{\\overline{\\mathsf{m}}}\n\\newcommand{\\pth}[2][\\!]{#1\\left({#2}\\right)}\n\\newcommand{\\polylog}{\\mathrm{polylog}} \\newcommand{\\N}{\\mathbb N}\n\\newcommand{\\Z}{\\mathbb Z} \\newcommand{\\pt}{p} \\newcommand{\\distY}[2]{\\left\\|\n{#1} - {#2} \\right\\|} \\newcommand{\\ptq}{q} \\newcommand{\\pts}{s}$ For an\nundirected graph $\\mathsf{G}=(\\mathsf{V}, \\mathsf{E})$, with $n$ vertices and\n$m$ edges, the \\emph{densest subgraph} problem, is to compute a subset $S\n\\subseteq \\mathsf{V}$ which maximizes the ratio $|\\mathsf{E}_S| / |S|$, where\n$\\mathsf{E}_S \\subseteq \\mathsf{E}$ is the set of all edges of $\\mathsf{G}$\nwith endpoints in $S$. The densest subgraph problem is a well studied problem\nin computer science. Existing exact and approximation algorithms for computing\nthe densest subgraph require $\\Omega(m)$ time. We present near-linear time (in\n$n$) approximation algorithms for the densest subgraph problem on\n\\emph{implicit} geometric intersection graphs, where the vertices are\nexplicitly given but not the edges. As a concrete example, we consider $n$\ndisks in the plane with arbitrary radii and present two different approximation\nalgorithms.","PeriodicalId":501570,"journal":{"name":"arXiv - CS - Computational Geometry","volume":"62 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Computational Geometry","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2405.18337","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
$ \newcommand{\cardin}[1]{\left| {#1} \right|}%
\newcommand{\Graph}{\Mh{\mathsf{G}}}% \providecommand{\G}{\Graph}%
\renewcommand{\G}{\Graph}% \providecommand{\GA}{\Mh{H}}%
\renewcommand{\GA}{\Mh{H}}% \newcommand{\VV}{\Mh{\mathsf{V}}}%
\newcommand{\VX}[1]{\VV\pth{#1}}% \providecommand{\EE}{\Mh{\mathsf{E}}}%
\renewcommand{\EE}{\Mh{\mathsf{E}}}% \newcommand{\Re}{\mathbb{R}}
\newcommand{\reals}{\mathbb{R}} \newcommand{\SetX}{\mathsf{X}}
\newcommand{\rad}{r} \newcommand{\Mh}[1]{#1} \newcommand{\query}{q}
\newcommand{\eps}{\varepsilon} \newcommand{\VorX}[1]{\mathcal{V} \pth{#1}}
\newcommand{\Polygon}{\mathsf{P}} \newcommand{\IntRange}[1]{[ #1 ]}
\newcommand{\Space}{\overline{\mathsf{m}}}
\newcommand{\pth}[2][\!]{#1\left({#2}\right)}
\newcommand{\polylog}{\mathrm{polylog}} \newcommand{\N}{\mathbb N}
\newcommand{\Z}{\mathbb Z} \newcommand{\pt}{p} \newcommand{\distY}[2]{\left\|
{#1} - {#2} \right\|} \newcommand{\ptq}{q} \newcommand{\pts}{s}$ For an
undirected graph $\mathsf{G}=(\mathsf{V}, \mathsf{E})$, with $n$ vertices and
$m$ edges, the \emph{densest subgraph} problem, is to compute a subset $S
\subseteq \mathsf{V}$ which maximizes the ratio $|\mathsf{E}_S| / |S|$, where
$\mathsf{E}_S \subseteq \mathsf{E}$ is the set of all edges of $\mathsf{G}$
with endpoints in $S$. The densest subgraph problem is a well studied problem
in computer science. Existing exact and approximation algorithms for computing
the densest subgraph require $\Omega(m)$ time. We present near-linear time (in
$n$) approximation algorithms for the densest subgraph problem on
\emph{implicit} geometric intersection graphs, where the vertices are
explicitly given but not the edges. As a concrete example, we consider $n$
disks in the plane with arbitrary radii and present two different approximation
algorithms.