Highly Accurate Description of Long-Range Interactions through the Combination of Neural Networks and Physical Models
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arXiv
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| Autores principales: | , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| _version_ | 1866917597735288832 |
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| author | Hong, Yingyue Huang, Jiayu Zhang, Dong H. |
| author_facet | Hong, Yingyue Huang, Jiayu Zhang, Dong H. |
| contents | We present a simple and general way to accurately describe long-range interactions between atoms and molecules through combining neural networks with physical models. Demonstrations on the H$_3$, Li$_3$ and 2KRb systems illustrate the exceptional extrapolation capabilities of the trained model, supported by underlying physical models. More importantly, the model exhibits high accuracy at energy scales below a few hundred millikelvin, where the reliability of $ab~initio$ methods diminishes. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2402_16287 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Highly Accurate Description of Long-Range Interactions through the Combination of Neural Networks and Physical Models Hong, Yingyue Huang, Jiayu Zhang, Dong H. Atomic Physics We present a simple and general way to accurately describe long-range interactions between atoms and molecules through combining neural networks with physical models. Demonstrations on the H$_3$, Li$_3$ and 2KRb systems illustrate the exceptional extrapolation capabilities of the trained model, supported by underlying physical models. More importantly, the model exhibits high accuracy at energy scales below a few hundred millikelvin, where the reliability of $ab~initio$ methods diminishes. |
| title | Highly Accurate Description of Long-Range Interactions through the Combination of Neural Networks and Physical Models |
| topic | Atomic Physics |
| url | https://arxiv.org/abs/2402.16287 |