The diatomic molecular spectroscopy database
POSTER
Abstract
We present an updated version of our previous website dedicated to the molecular spectroscopy of diatomic molecules (https://rios.mp.fhi.mpg.de/index.php): A user-friendly website including spectroscopic constants of diatomic molecules beyond Herzberg's book and the NIST website. It is open, so researchers can register and upload new spectroscopic data to make a dynamic and up-to-date database for the community. The data is freely available and ready to be downloaded in any preferable format. The updated version incorporates a graphical user interface to perform machine learning studies with the data. The user can select any feature and train a machine-learning model to predict a given outcome. Therefore, in this way, bringing machine learning closer to spectroscopy. Similarly, we include more advanced plotting tools for a better user experience.
Presenters
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Daniel Julian
Department of Physics and Astronomy, Stony Brook Univeristy
Authors
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Daniel Julian
Department of Physics and Astronomy, Stony Brook Univeristy
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Connor Chin
Department of Physics and Astronomy, Stony Brook University
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Ethan Franco
Department of Physics and Astronomy, Stony Brook Univeristy
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James Marini
Department of Physics and Astronomy, Stony Brook Univeristy
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Yueqian Wang
Department of Physics and Astronomy, Stony Brook Univeristy
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Jesus Perez Rios
Stony Brook University