A comparison of extremal optimization with flat-histogram dynamics for finding spin-glass ground states
arXiv:cond-mat/0210075 · doi:10.1143/JPSJ.72.1380
Abstract
We compare the performance of extremal optimization (EO), flat-histogram and equal-hit algorithms for finding spin-glass ground states. The first-passage-times to a ground state are computed. At optimal parameter of tau=1.15, EO outperforms other methods for small system sizes, but equal-hit algorithm is competitive to EO, particularly for large systems. Flat-histogram and equal-hit algorithms offer additional advantage that they can be used for equilibrium thermodynamic calculations. We also propose a method to turn EO into a useful algorithm for equilibrium calculations. Keywords: extremal optimization. flat-histogram algorithm, equal-hit algorithm, spin-glass model, ground state.
10 LaTeX pages, 2 figures
References in corpus (15)
- Exchange Monte Carlo Method and Application to Spin Glass Simulations
- Multicanonical Ensemble: A New Approach to Simulate First-order Phase Transitions
- Optimization with Extremal Dynamics
- Nature's Way of Optimizing
- Transition Matrix Monte Carlo Method
- Monte Carlo simulation and global optimization without parameters
- Multi-Overlap Simulations of the Edwards-Anderson Ising Spin Glass
- Faster Monte Carlo Simulations at Low Temperatures. The Waiting Time Method
- Renormalization for Discrete Optimization
- Evidence for existence of many pure ground states in 3d Spin Glasses
- Is the broad histogram random walk dynamics correct?
- Transition Matrix Monte Carlo
- Configuration Space for Random Walk Dynamics
- A new approach to the study of the ground-state properties of 2D Ising spin glass
- A general learning algorithm for solving optimization problems and its application to the spin glass problem