Article Dans Une Revue Journal of Statistical Mechanics: Theory and Experiment Année : 2022

Aligning random graphs with a sub-tree similarity message-passing algorithm

Résumé

The problem of aligning Erdős–Rényi random graphs is a noisy, average-case version of the graph isomorphism problem, in which a pair of correlated random graphs is observed through a random permutation of their vertices. We study a polynomial time message-passing algorithm devised to solve the inference problem of partially recovering the hidden permutation, in the sparse regime with constant average degrees. We perform extensive numerical simulations to determine the range of parameters in which this algorithm achieves partial recovery. We also introduce a generalized ensemble of correlated random graphs with prescribed degree distributions, and extend the algorithm to this case.

Dates et versions

hal-04986824 , version 1 (11-03-2025)

Identifiants

Citer

Giovanni Piccioli, Guilhem Semerjian, Gabriele Sicuro, Lenka Zdeborová. Aligning random graphs with a sub-tree similarity message-passing algorithm. Journal of Statistical Mechanics: Theory and Experiment, 2022, 2022 (6), pp.063401. ⟨10.1088/1742-5468/ac70d2⟩. ⟨hal-04986824⟩
30 Consultations
0 Téléchargements

Altmetric

Partager

  • More