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High Efficiency Configuration Space Sampling -- probing the distribution of available states

by Paweł T. Jochym, Jan Łażewski

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Submission summary

Authors (as registered SciPost users): Paweł Jochym · Jan Łażewski
Submission information
Preprint Link: scipost_202101_00011v3  (pdf)
Date accepted: 2021-05-26
Date submitted: 2021-05-21 10:49
Submitted by: Jochym, Paweł
Submitted to: SciPost Physics
Ontological classification
Academic field: Physics
  • Condensed Matter Physics - Theory
Approaches: Theoretical, Computational


Substantial acceleration of research and more efficient utilization of resources can be achieved in modelling 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 non-zero temperatures. In contrast to the methods based on molecular dynamics, where only a small fraction of obtained data is used, the proposed scheme is distinguished by a considerably higher, reaching even 80%, acceptance ratio and much lower amount of computation required to obtain adequate sampling of the system in thermal equilibrium at non-zero temperature.

Author comments upon resubmission

Following the comments of the referees and editor request we have corrected the mistake in the caption of the Fig. 5 and added a sentence indicating promising future direction of development for the proposed method.

List of changes

- Caption of the Fig. 5 corrected
- Sentence on future research direction added

Published as SciPost Phys. 10, 129 (2021)

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