Rostock 2019 – scientific programme

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A: Fachverband Atomphysik

A 10: Highly charged ions and their applications

A 10.2: Talk

Monday, March 11, 2019, 16:30–16:45, S HS 3 Physik

Statistical completion and validation of the NIST Atomic Spectral Database — •Keisuke Fujii¹ and José R. Crespo López-Urrutia² — ¹Kyoto University, Department of Mechanical Engineering and Science, Graduate School of Engineering, Kyoto 615-8540, Japan — ²Max-Planck-Institut für Kernphysik, Saupfercheckweg 1, 69117 Heidelberg, Germany

The NIST Atomic Spectral Database (ASD) [1] contains the electronic energy levels of most elements in all known degrees of ionization, and has for decades been an essential standard tool in atomic science, spectroscopy and plasma physics. However, there are substantial gaps in the data, and many energy levels of highly charged ions are still missing owing to the difficulties of measurements. In this work, we utilize a machine learning method to find structures in the atomic data compiled in the ASD database. With the extracted data structure, we predict the missing data values and provide probabilistic Bayesian uncertainty information. Furthermore, we identify some anomalies in the existing entries, which may be due to typographic mistakes or misidentifications.

[1] Kramida, A., Ralchenko, Yu., Reader, J. and NIST ASD Team (2018). NIST Atomic Spectra Database (version 5.6.1), https://physics.nist.gov/asd . National Institute of Standards and Technology, Gaithersburg, MD. DOI: https://doi.org/10.18434/T4W30F