Twins in rotational spectroscopy: Does a rotational spectrum uniquely identify a molecule?
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arXiv
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| Main Authors: | , , , , , |
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| Format: | Preprint |
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2024
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| _version_ | 1866916195515498496 |
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| author | Schwarting, Marcus Seifert, Nathan A. Davis, Michael J. Blaiszik, Ben Foster, Ian Prozument, Kirill |
| author_facet | Schwarting, Marcus Seifert, Nathan A. Davis, Michael J. Blaiszik, Ben Foster, Ian Prozument, Kirill |
| contents | Rotational spectroscopy is the most accurate method for determining structures of molecules in the gas phase. It is often assumed that a rotational spectrum is a unique "fingerprint" of a molecule. The availability of large molecular databases and the development of artificial intelligence methods for spectroscopy makes the testing of this assumption timely. In this paper, we pose the determination of molecular structures from rotational spectra as an inverse problem. Within this framework, we adopt a funnel-based approach to search for molecular twins, which are two or more molecules, which have similar rotational spectra but distinctly different molecular structures. We demonstrate that there are twins within standard levels of computational accuracy by generating rotational constants for many molecules from several large molecular databases, indicating the inverse problem is ill-posed. However, some twins can be distinguished by increasing the accuracy of the theoretical methods or by performing additional experiments. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_04225 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Twins in rotational spectroscopy: Does a rotational spectrum uniquely identify a molecule? Schwarting, Marcus Seifert, Nathan A. Davis, Michael J. Blaiszik, Ben Foster, Ian Prozument, Kirill Chemical Physics Machine Learning Rotational spectroscopy is the most accurate method for determining structures of molecules in the gas phase. It is often assumed that a rotational spectrum is a unique "fingerprint" of a molecule. The availability of large molecular databases and the development of artificial intelligence methods for spectroscopy makes the testing of this assumption timely. In this paper, we pose the determination of molecular structures from rotational spectra as an inverse problem. Within this framework, we adopt a funnel-based approach to search for molecular twins, which are two or more molecules, which have similar rotational spectra but distinctly different molecular structures. We demonstrate that there are twins within standard levels of computational accuracy by generating rotational constants for many molecules from several large molecular databases, indicating the inverse problem is ill-posed. However, some twins can be distinguished by increasing the accuracy of the theoretical methods or by performing additional experiments. |
| title | Twins in rotational spectroscopy: Does a rotational spectrum uniquely identify a molecule? |
| topic | Chemical Physics Machine Learning |
| url | https://arxiv.org/abs/2404.04225 |