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ChiantiPy: a Python package for Astrophysical Spectroscopy

Authors: Will T. Barnes; Kenneth P. Dere;

ChiantiPy: a Python package for Astrophysical Spectroscopy

Abstract

ChiantiPy is an interface to the CHIANTI atomic database for astrophysical spectroscopy. The highly-cited CHIANTI project, now in its 20th year, is an invaluable resource to the solar physics community. The ChiantiPy project brings the power of the scientific Python stack to the CHIANTI database, allowing solar physicists and astronomers to easily make use of this atomic data and calculate commonly used quantities from it such as radiative loss rates and emissivities for particular atomic transitions. In this talk, we will briefly discuss the history of the CHIANTI database and the ChiantiPy project as well as the current state of the project and its place in the solar physics community. We will demonstrate some of the capabilities of the ChiantiPy code and show examples of how ChiantiPy can be used in both modeling and observational studies. Finally, we'll discuss how ChiantiPy helps to bring the power of the CHIANTI atomic database to the growing set of astronomy-related tools in Python.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
hybrid