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Sequential Stub Matching for Asymptotically Uniform Generation of Directed Graphs with a Given Degree Sequence

Title: Sequential Stub Matching for Asymptotically Uniform Generation of Directed Graphs with a Given Degree Sequence
Authors: van Ieperen, Femke; Kryven, Ivan; Sub Mathematical Modeling; Mathematical Modeling
Publication Year: 2025
Subject Terms: 05C20; 05C80; 68W20; 68W25; Directed graphs; Random graphs; Randomised approximation algorithms; Discrete Mathematics and Combinatorics
Description: We discuss sequential stub matching for directed graphs and show that this process can be used to sample simple digraphs with asymptotically equal probability. The process starts with an empty edge set and repeatedly adds edges to it with a certain state-dependent bias until the desired degree sequence is fulfilled, whilst avoiding placing a double edge or self-loop. We show that uniform sampling is achieved in the sparse regime when the maximum degree dmax is asymptotically dominated by m1/4, where m is the number of edges. The proof is based on deriving various combinatorial estimates related to the number of digraphs with a given degree sequence and controlling concentration of these estimates in large digraphs. This suggests that sequential stub matching can be viewed as a practical algorithm for almost uniform sampling of digraphs. We show that this algorithm can be implemented to feature a linear expected runtime O(m).
Document Type: article in journal/newspaper
File Description: application/pdf
Language: English
ISSN: 0218-0006
Relation: https://dspace.library.uu.nl/handle/1874/472490
Availability: https://dspace.library.uu.nl/handle/1874/472490
Rights: info:eu-repo/semantics/OpenAccess
Accession Number: edsbas.F7AB6B6C
Database: BASE