A novel Bayesian approach to the computation of the configurational density of states
Moreno, Felipe, Sergio M. Davis, Joaquín Peralta · arXiv (Cornell University) · 2021
In this work we develop and implement a novel Bayesian method for computing the DOS of a system. This method is based on the use of a test function with adjustable parameters and we use Bayes theorem to find the best parameters given a certain number of measurements done on the system. This measurements can be done in any ensemble defined by a distribution function. We found that the algorithm can find the DOS in a reasonable amount of time, and that if the test function is suitable enough, the DOS found by the algorithm is very close to the true DOS.