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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

  • Daniel Julian

    Department of Physics and Astronomy, Stony Brook Univeristy

Authors

  • Daniel Julian

    Department of Physics and Astronomy, Stony Brook Univeristy

  • Connor Chin

    Department of Physics and Astronomy, Stony Brook University

  • Ethan Franco

    Department of Physics and Astronomy, Stony Brook Univeristy

  • James Marini

    Department of Physics and Astronomy, Stony Brook Univeristy

  • Yueqian Wang

    Department of Physics and Astronomy, Stony Brook Univeristy

  • Jesus Perez Rios

    Stony Brook University