Multiple Histogram Method and Static Monte Carlo Sampling

Flat histogram Monte Carlo method

We discuss a sampling algorithm which generates flat histogram in energy. In combination with transition matrix Monte Carlo, the density of states and derived quantities such as entropy and free energy as a function of temperature can be computed in a single simulation.

Modified Monte Carlo with Importance Sampling Method

Monte Carlo simulation methods apply a random sampling and modifications can be made of this method is by using variance reduction techniques (VRT). VRT objective is to reduce the variance due to Monte Carlo methods become more accurate with a variance approaching zero and the number of samples approaches infinity, which is not practical in the real situation (Chen, 2004). These techniques are ...

Error estimation in the histogram Monte Carlo method

SFI WORKING PAPER: 1998-04-035 SFI Working Papers contain accounts of scientific work of the author(s) and do not necessarily represent the views of the Santa Fe Institute. We accept papers intended for publication in peer-reviewed journals or proceedings volumes, but not papers that have already appeared in print. Except for papers by our external faculty, papers must be based on work done at ...

Christiane Lemieux Monte Carlo and Quasi - Monte Carlo Sampling

Cost-Driven Multiple Importance Sampling for Monte-Carlo Rendering

The global illumination or transport problems can also be considered as a sequence of integrals, while its MonteCarlo solutions as different sampling techniques. Multiple importance sampling takes advantage of different sampling strategies and combines the results obtained with them. In this paper we propose the combination of very different global illumination algorithms in a way that their st...