A Bayesian framework is developed to reconstruct the density of states from multiple canonical simulations. The framework encompasses the histogram reweighting method of Ferrenberg and Swendsen. The new approach applies to nonparametric as well as parametric models and does not require simulation data to be discretized. It offers a means to assess the precision of the reconstructed density of states and of derived thermodynamic quantities.
| Author(s): | Habeck, M. |
| Journal: | Physical Review Letters |
| Volume: | 98 |
| Number (issue): | 20, 200601 |
| Pages: | 1-4 |
| Year: | 2007 |
| Month: | May |
| Day: | 0 |
| Bibtex Type: | Article (article) |
| DOI: | 10.1103/PhysRevLett.98.200601 |
| Digital: | 0 |
| Electronic Archiving: | grant_archive |
| Language: | en |
| Organization: | Max-Planck-Gesellschaft |
| School: | Biologische Kybernetik |
| Links: | |
BibTex
@article{4487,
title = {Bayesian Reconstruction of the Density of States},
journal = {Physical Review Letters},
abstract = {A Bayesian framework is developed to reconstruct the density of states from multiple canonical simulations. The framework encompasses the histogram reweighting method of Ferrenberg and Swendsen. The new approach applies to nonparametric as well as parametric models and does not require simulation data to be discretized. It offers a means to assess the precision of the reconstructed density of states and of derived thermodynamic quantities.},
volume = {98},
number = {20, 200601},
pages = {1-4},
organization = {Max-Planck-Gesellschaft},
school = {Biologische Kybernetik},
month = may,
year = {2007},
slug = {4487},
author = {Habeck, M.},
month_numeric = {5}
}