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Algorithms and Turing kernels for detecting and counting small patterns in unit disk graphs

Title: Algorithms and Turing kernels for detecting and counting small patterns in unit disk graphs
Authors: Nederlof, Jesper; Szilágyi, Krisztina; Sub Algorithms and Complexity; Algorithms and Complexity
Publication Year: 2025
Subject Terms: Parameterized complexity; Subgraph isomorphism; Unit disk graphs; Theoretical Computer Science; General Computer Science; Computer Networks and Communications; Computational Theory and Mathematics; Applied Mathematics
Description: In this paper we investigate the parameterized complexity of counting and detecting small patterns in unit disk graphs: Given an n-vertex unit disk graph G with an embedding of ply p (i.e. G is an intersection graph of closed unit disks, and each point is contained in at most p disks) and a k-vertex unit disk graph P, count the number of (induced) copies of P in G. For general patterns P, we give an 2O(pk/log⁡k)nO(1) time algorithm for counting pattern occurrences. We show this is tight, even for ply p=2: any 2o(n/log⁡n)nO(1) time algorithm violates the Exponential Time Hypothesis (ETH). Our approach combines tools developed for planar subgraph isomorphism such as ‘efficient inclusion-exclusion’ from Nederlof (2020) [15], and ‘isomorphisms checks’ from Bodlaender et al. (2016) [5] with a different separator hierarchy and a new bound on the number of non-isomorphic separations tailored for unit disk graphs.
Document Type: article in journal/newspaper
File Description: application/pdf
Language: English
ISSN: 0022-0000
Relation: https://dspace.library.uu.nl/handle/1874/474081
Availability: https://dspace.library.uu.nl/handle/1874/474081
Rights: info:eu-repo/semantics/OpenAccess
Accession Number: edsbas.BBD59DBB
Database: BASE