Transition Matrix Monte Carlo
arXiv:cond-mat/9908461 · doi:10.1142/S0129183199001340
Abstract
Although histogram methods have been extremely effective for analyzing data from Monte Carlo simulations, they do have certain limitations, including the range over which they are valid and the difficulties of combining data from independent simulations. In this paper, we describe an complementary approach to extracting information from Monte Carlo simulations that uses the matrix of transition probabilities. Combining the Transition Matrix with an N-fold way simulation technique produces an extremely flexible and efficient approach to rather general Monte Carlo simulations.
Maui Conference on Statistical Physics
References in corpus (2)
Cited by in corpus (7)
- Determining the density of states for classical statistical models: A random walk algorithm to produce a flat histogram
- Transition Matrix Monte Carlo Method
- Flat histogram Monte Carlo method
- An Introduction to Monte Carlo Simulation of Statistical physics Problem
- A comparison of extremal optimization with flat-histogram dynamics for finding spin-glass ground states
- Flat histogram method comparison on 2D Ising Model
- Stochastic Approximation Monte Carlo with a Dynamic Update Factor