Finding long cycles in graphs
Statistical Mechanics
2007-07-03 v1 Disordered Systems and Neural Networks
Computational Complexity
Probability
Abstract
We analyze the problem of discovering long cycles inside a graph. We propose and test two algorithms for this task. The first one is based on recent advances in statistical mechanics and relies on a message passing procedure. The second follows a more standard Monte Carlo Markov Chain strategy. Special attention is devoted to Hamiltonian cycles of (non-regular) random graphs of minimal connectivity equal to three.
Cite
@article{arxiv.cond-mat/0702613,
title = {Finding long cycles in graphs},
author = {Enzo Marinari and Guilhem Semerjian and Valery Van Kerrebroeck},
journal= {arXiv preprint arXiv:cond-mat/0702613},
year = {2007}
}