English

Ground-State Entropy of the Random Vertex-Cover Problem

Disordered Systems and Neural Networks 2009-03-17 v2

Abstract

Counting the number of ground states for a spin-glass or NP-complete combinatorial optimization problem is even more difficult than the already hard task of finding a single ground state. In this paper the entropy of minimum vertex-covers of random graphs is estimated through a set of iterative equations based on the cavity method of statistical mechanics. During the iteration both the cavity entropy contributions and cavity magnetizations for each vertex are updated. This approach overcomes the difficulty of iterative divergence encountered in the zero temperature first-step replica-symmetry-breaking (1RSB) spin-glass theory. It is still applicable when the 1RSB mean-field theory is no longer stable. The method can be extended to compute the entropies of ground-states and metastable minimal-energy states for other random-graph spin-glass systems.

Keywords

Cite

@article{arxiv.0810.0584,
  title  = {Ground-State Entropy of the Random Vertex-Cover Problem},
  author = {Jie Zhou and Haijun Zhou},
  journal= {arXiv preprint arXiv:0810.0584},
  year   = {2009}
}

Comments

4 pages, 2 figures. Final version as appear in PRE

R2 v1 2026-06-21T11:27:00.067Z