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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 |
| Specialties: |
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| Approaches: | Theoretical, Computational |
Abstract
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
List of changes
- Caption of the Fig. 5 corrected
- Sentence on future research direction added
Published as SciPost Phys. 10, 129 (2021)