Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2501.11370 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866912912251027456 |
|---|---|
| author | Maillard, Lune Finocchi, Fabio Godinho, César Trassinelli, Martino |
| author_facet | Maillard, Lune Finocchi, Fabio Godinho, César Trassinelli, Martino |
| contents | Lennard-Jones clusters, while an easy system, have a significant number of non equivalent configurations that increases rapidly with the number of atoms in the cluster. Here, we aim at determining the cluster partition function; we use the nested sampling algorithm, which transforms the multidimensional integral into a one-dimensional one, to perform this task. In particular, we use the nested_fit program, which implements slice sampling as search algorithm. We study here the 7-atom and 36-atom clusters to benchmark nested_fit for the exploration of potential energy surfaces. We find that nested_fit is able to recover phase transitions and find different stable configurations of the cluster. Furthermore, the implementation of the slice sampling algorithm has a clear impact on the computational cost. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_11370 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Nested Sampling for Exploring Lennard-Jones Clusters Maillard, Lune Finocchi, Fabio Godinho, César Trassinelli, Martino Computational Physics Lennard-Jones clusters, while an easy system, have a significant number of non equivalent configurations that increases rapidly with the number of atoms in the cluster. Here, we aim at determining the cluster partition function; we use the nested sampling algorithm, which transforms the multidimensional integral into a one-dimensional one, to perform this task. In particular, we use the nested_fit program, which implements slice sampling as search algorithm. We study here the 7-atom and 36-atom clusters to benchmark nested_fit for the exploration of potential energy surfaces. We find that nested_fit is able to recover phase transitions and find different stable configurations of the cluster. Furthermore, the implementation of the slice sampling algorithm has a clear impact on the computational cost. |
| title | Nested Sampling for Exploring Lennard-Jones Clusters |
| topic | Computational Physics |
| url | https://arxiv.org/abs/2501.11370 |