Boltzmann sampling and optimal exact-size sampling for directed acyclic graphs

Fuente: arXiv
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Autori principali: Gabryelski, Wojciech, Gołȩbiewski, Zbigniew, Pépin, Martin
Natura: Preprint
Pubblicazione: 2026
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author Gabryelski, Wojciech
Gołȩbiewski, Zbigniew
Pépin, Martin
author_facet Gabryelski, Wojciech
Gołȩbiewski, Zbigniew
Pépin, Martin
contents We propose two efficient algorithms for generating uniform random directed acyclic graphs, including an asymptotically optimal exact-size sampler that performs $\frac{n^2}{2} + o(n^2)$ operations and requests to a random generator. This was achieved by extending the Boltzmann model for graphical generating functions and by using various decompositions of directed acyclic graphs. The presented samplers improve upon the state-of-the-art algorithms in terms of theoretical complexity and offer a significant speed-up in practice.
format Preprint
id arxiv_https___arxiv_org_abs_2602_08471
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Boltzmann sampling and optimal exact-size sampling for directed acyclic graphs
Gabryelski, Wojciech
Gołȩbiewski, Zbigniew
Pépin, Martin
Data Structures and Algorithms
Discrete Mathematics
Combinatorics
68R05, 68R10, 05A15, 68W40
G.2.1; G.2.2; F.2.2
We propose two efficient algorithms for generating uniform random directed acyclic graphs, including an asymptotically optimal exact-size sampler that performs $\frac{n^2}{2} + o(n^2)$ operations and requests to a random generator. This was achieved by extending the Boltzmann model for graphical generating functions and by using various decompositions of directed acyclic graphs. The presented samplers improve upon the state-of-the-art algorithms in terms of theoretical complexity and offer a significant speed-up in practice.
title Boltzmann sampling and optimal exact-size sampling for directed acyclic graphs
topic Data Structures and Algorithms
Discrete Mathematics
Combinatorics
68R05, 68R10, 05A15, 68W40
G.2.1; G.2.2; F.2.2
url https://arxiv.org/abs/2602.08471