On the Free Energy Monte Carlo algorithm
M.J. Thill
TL;DR
This paper explores the Free Energy Monte Carlo algorithm, demonstrating its ability to address ergodicity issues, determine entropy functions, and explore energy landscapes in statistical systems.
Contribution
It provides a detailed investigation of the Free Energy Monte Carlo algorithm, highlighting its applications in entropy calculation and energy landscape exploration.
Findings
Effective in calculating entropy functions
Capable of exploring energy minima
Addresses ergodicity problems in Monte Carlo simulations
Abstract
In this paper, I investigate more closely the recently proposed Free Energy Monte Carlo algorithm that is devised in particular for calculations where conventional Monte Carlo simulations struggle with ergodicity problems. The simplest version of the proposed algorithm allows for the determination of the entropy function of statistical systems and/or performs entropy sampling at sufficiently large times. I also show how this algorithm can be used to explore the system's energy space, in particular for minima.
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Taxonomy
TopicsStatistical Mechanics and Entropy · Theoretical and Computational Physics · Complex Systems and Time Series Analysis