Generalized Ensemble Simulations for Complex Systems
arXiv:cond-mat/0110521 · doi:10.1016/S0010-4655(02)00203-5
Abstract
The most efficient MC weights for the calculation of physical, canonical expectation values are not necessarily those of the canonical ensemble. The use of suitably generalized ensembles can lead to a much faster convergence of the simulation. Although not realized by nature, these ensembles can be implemented on computers. In recent years generalized ensembles have in particular been studied for the simulation of complex systems. For these systems it is typical that conflicting constraints lead to free energy barriers, which fragment the configuration space. Examples of major interest are spin glasses and proteins. In my overview I first comment on the strengths and weaknesses of a few major approaches, multicanonical simulations, transition variable methods, and parallel tempering. Subsequently, two applications are presented: a new analysis of the Parisi overlap distribution for the 3d Edwards-Anderson Ising spin glass and the helix-coil transition of amino-acid homo-oligomers.
Plenary talk at the CCP 2001 conference, submitted to Comp. Phys. Commun., 7 pages, 3 figures, some typos eliminated
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- Fast Flat-Histogram Method for Generalized Spin Models
- Fluctuating temperature outside superstatistics: thermodynamics of small systems
- A simple protocol for the probability weights of the simulated tempering algorithm: applications to first-order phase transitions
- Monte Carlo SImulation of Polymers: Coarse-Grained Models
- Finite-size scaling of Monte Carlo simulations for the fcc Ising antiferromagnet: Effects of the low-temperature phase degeneracy
- A classification of nonequilibrium steady states based on temperature correlations