Optimized Monte Carlo Methods
arXiv:cond-mat/9612010
Abstract
I discuss optimized data analysis and Monte Carlo methods. Reweighting methods are discussed through examples, like Lee-Yang zeroes in the Ising model and the absence of deconfinement in QCD. I discuss reweighted data analysis and multi-hystogramming. I introduce Simulated Tempering, and as an example its application to the Random Field Ising Model. I illustrate Parallel Tempering, and discuss some technical crucial details like thermalization and volume scaling. I give a general perspective by discussing Umbrella Methods and the Multicanonical approach.
Lectures given at the 1996 Budapest Summer School on Monte Carlo Methods. 35 pages including 17 figures
References in corpus (6)
- Simulated Tempering: A New Monte Carlo Scheme
- Multicanonical Ensemble: A New Approach to Simulate First-order Phase Transitions
- A New Approach to Spin Glass Simulations
- Multicanonical Study of the 3D Ising Spin Glass
- Tempering Dynamics and Relaxation Times in the Ising Model
- Chaos in short-range spin glasses