Monte Carlo simulation and global optimization without parameters
凝聚态物理
2016-08-31 v1
摘要
We propose a new ensemble for Monte Carlo simulations, in which each state is assigned a statistical weight , where is the number of states with smaller or equal energy. This ensemble has robust ergodicity properties and gives significant weight to the ground state, making it effective for hard optimization problems. It can be used to find free energies at all temperatures and picks up aspects of critical behaviour (if present) without any parameter tuning. We test it on the travelling salesperson problem, the Edwards-Anderson spin glass and the triangular antiferromagnet.
引用
@article{arxiv.cond-mat/9501114,
title = {Monte Carlo simulation and global optimization without parameters},
author = {Bobby Hesselbo and R. B. Stinchcombe},
journal= {arXiv preprint arXiv:cond-mat/9501114},
year = {2016}
}
备注
10 pages with 3 Postscript figures, to appear in Phys. Rev. Lett.