Report on scipost_202101_00011v1
Paweł T. Jochym, Jan Łażewski · 2021
Substantial acceleration of research and more efficient utilization of resources can be achieved in modeling investigated phenomena by identifying the limits of system's accessible states instead of tracing the trajectory of its evolution.The proposed strategy uses the Metropolis-Hastings Monte-Carlo sampling of the configuration space probability distribution coupled with physically-motivated prior probability distribution.We demonstrate this general idea by presenting a high performance method of generating configurations for lattice dynamics and other computational solid state physics calculations corresponding to nonzero temperatures.In contrast to the methods based on molecular dynamics, where only a small fraction of obtained data is consumed, the proposed scheme is distinguished by a considerably higher, reaching even 80%, acceptance ratio.