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Bibliographic Details
Main Authors: Hébert-Johnson, Úrsula, Lokshtanov, Daniel
Format: Preprint
Published: 2025
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Online Access:https://arxiv.org/abs/2501.05024
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author Hébert-Johnson, Úrsula
Lokshtanov, Daniel
author_facet Hébert-Johnson, Úrsula
Lokshtanov, Daniel
contents We design an algorithm that generates an $n$-vertex unlabeled chordal graph uniformly at random in expected polynomial time. Along the way, we develop the following two results: (1) an $\mathsf{FPT}$ algorithm for counting and sampling labeled chordal graphs with a given automorphism $π$, parameterized by the number of moved points of $π$, and (2) a proof that the probability that a random $n$-vertex labeled chordal graph has a given automorphism $π\in S_n$ is at most $1/2^{c\max\{μ^2,n\}}$, where $μ$ is the number of moved points of $π$ and $c$ is a constant. Our algorithm for sampling unlabeled chordal graphs calls the aforementioned $\mathsf{FPT}$ algorithm as a black box with potentially large values of the parameter $μ$, but the probability of calling this algorithm with a large value of $μ$ is exponentially small.
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publishDate 2025
record_format arxiv
spellingShingle Sampling Unlabeled Chordal Graphs in Expected Polynomial Time
Hébert-Johnson, Úrsula
Lokshtanov, Daniel
Data Structures and Algorithms
We design an algorithm that generates an $n$-vertex unlabeled chordal graph uniformly at random in expected polynomial time. Along the way, we develop the following two results: (1) an $\mathsf{FPT}$ algorithm for counting and sampling labeled chordal graphs with a given automorphism $π$, parameterized by the number of moved points of $π$, and (2) a proof that the probability that a random $n$-vertex labeled chordal graph has a given automorphism $π\in S_n$ is at most $1/2^{c\max\{μ^2,n\}}$, where $μ$ is the number of moved points of $π$ and $c$ is a constant. Our algorithm for sampling unlabeled chordal graphs calls the aforementioned $\mathsf{FPT}$ algorithm as a black box with potentially large values of the parameter $μ$, but the probability of calling this algorithm with a large value of $μ$ is exponentially small.
title Sampling Unlabeled Chordal Graphs in Expected Polynomial Time
topic Data Structures and Algorithms
url https://arxiv.org/abs/2501.05024