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Atoms 2017, 5(3), 31; doi:10.3390/atoms5030031

Radiative and Collisional Molecular Data and Virtual Laboratory Astrophysics

1
Institute of Physics, Belgrade University, Pregrevica 118, Zemun, 11080 Belgrade, Serbia
2
Astronomical Observatory, Volgina 7, 11060 Belgrade, Serbia
3
Faculty of Organizational Sciences, University of Belgrade, Jove Ilica 154, 11000 Belgrade, Serbia
4
LERMA, Observatoire de Paris, UMR CNRS 8112, UPMC, 92195 Meudon CEDEX, France
*
Author to whom correspondence should be addressed.
Academic Editor: Elmar Träbert
Received: 4 September 2017 / Revised: 12 September 2017 / Accepted: 13 September 2017 / Published: 19 September 2017
(This article belongs to the Special Issue Spectral Line Shapes in Astrophysics and Related Topics)
View Full-Text   |   Download PDF [597 KB, uploaded 19 September 2017]   |  

Abstract

Spectroscopy has been crucial for our understanding of physical and chemical phenomena. The interpretation of interstellar line spectra with radiative transfer calculations usually requires two kinds of molecular input data: spectroscopic data (such as energy levels, statistical weights, transition probabilities, etc.) and collision data. This contribution describes how such data are collected, stored, and which limitations exist. Also, here we summarize challenges of atomic/molecular databases and point out our experiences, problems, etc., which we are faced with. We present overview of future developments and needs in the areas of radiative transfer and molecular data. View Full-Text
Keywords: atomic/molecular data; radiative and collisional processes; stars atomic/molecular data; radiative and collisional processes; stars
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Srećković, V.A.; Ignjatović, L.M.; Jevremović, D.; Vujčić, V.; Dimitrijević, M.S. Radiative and Collisional Molecular Data and Virtual Laboratory Astrophysics. Atoms 2017, 5, 31.

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