Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Benchmarking Current Capabilities for the Generation of Excitation and Photoionisation Atomic Data

Catherine Ramsbottom
* ,
Connor Ballance
,
Ryan Smyth
,
Andrew Conroy
ORCID logo ,
Luis Fernández-Menchero
ORCID logo ,
Michael Turkington
,
Francis Keenan
ORCID logo
Version 1 : Received: 25 June 2018 / Approved: 26 June 2018 / Online: 26 June 2018 (11:41:44 CEST)

A peer-reviewed article of this Preprint also exists.

Ramsbottom, C.; Ballance, C.; Smyth, R.; Conroy, A.; Fernández-Menchero, L.; Turkington, M.; Keenan, F. Benchmarking Current Capabilities for the Generation of Excitation and Photoionisation Atomic Data. Galaxies 2018, 6, 90. Ramsbottom, C.; Ballance, C.; Smyth, R.; Conroy, A.; Fernández-Menchero, L.; Turkington, M.; Keenan, F. Benchmarking Current Capabilities for the Generation of Excitation and Photoionisation Atomic Data. Galaxies 2018, 6, 90.

Abstract

The spectra currently emerging from modern ground- and space-based astronomical instruments are of exceptionally high quality and resolution. To meaningfully analyse these spectra researchers utilise complex modelling codes to replicate the observations. The main inputs to these codes are atomic data such as excitation and photoionisation cross sections as well as radiative transition probabilities, energy levels and line strengths. In this publication the current capabilities of the numerical methods and computer packages used in the generation of these data are discussed. Particular emphasis is given to Fe-peak species and the heavy systems of tungsten and molybdenum. Some of the results presented to highlight certain issues and/or advances have already been published in the literature, while other sections present, for the first time, new recently evaluated atomic data.

Keywords

R-matrix; atomic data; atomic processes; collisions; Fe-peak elements; electron-impact excitation; photoionization

Subject

Physical Sciences, Nuclear and High Energy Physics

Copyright: 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.

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