Approaching the ground states of the random maximum two-satisfiability problem by a greedy single-spin flipping process
Disordered Systems and Neural Networks
2012-04-10 v1
Abstract
In this brief report we explore the energy landscapes of two spin glass models using a greedy single-spin flipping process, {\tt Gmax}. The ground-state energy density of the random maximum two-satisfiability problem is efficiently approached by {\tt Gmax}. The achieved energy density decreases with the evolution time as with a small prefactor and a scaling coefficient , indicating an energy landscape with deep and rugged funnel-shape regions. For the Viana-Bray spin glass model, however, the greedy single-spin dynamics quickly gets trapped to a local minimal region of the energy landscape.
Cite
@article{arxiv.1104.2656,
title = {Approaching the ground states of the random maximum two-satisfiability problem by a greedy single-spin flipping process},
author = {Hui Ma and Haijun Zhou},
journal= {arXiv preprint arXiv:1104.2656},
year = {2012}
}
Comments
5 pages with 4 figures included. Accepted for publication in Physical Review E as a brief report