New tool in python for spectroscopic data analysis: Application to variable stars data from the Oukaimden and OHP observatories
Recently we have carried out a campaign of measurements of variable star spectra at the Oukaimeden observatory since 2013. To analyze thousands of spectra, we developed a graphical interface using Python. The spectroscopic study of variable stars is based on the acquisition of data in the observator...
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Veröffentlicht in: | Astronomy and computing 2023-04, Vol.43, p.100708, Article 100708 |
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Sprache: | eng |
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Zusammenfassung: | Recently we have carried out a campaign of measurements of variable star spectra at the Oukaimeden observatory since 2013. To analyze thousands of spectra, we developed a graphical interface using Python.
The spectroscopic study of variable stars is based on the acquisition of data in the observatory, and their storage in Fits files. We treat this data digitally to make them exploitable and graphically representable, for this purpose we use special software or scripts developed by astrophysicists. To facilitate analysis and meet our needs, we developed a graphical interface using Python and used the Tkinter module to represent our spectroscopic data graphically. This interface can plot figures of our spectra in 1D curve, and as a superposition in 1D and 2D. Thus, this interface can determine the necessary parameters in the spectroscopic study of short-period variable stars; such as the pulsation phases, the Blazhko phase, the correction for the heliocentric velocity, etc. Moreover, we can use this interface to convert the pre-treated Fits files into text files as well as to create Excel tables containing the calculated parameters. This interface is easy and fast to use and can provide high-quality figures.
By exploiting the potential of this graphical interface, we were able to carry out a study of the influence of the Blazhko effect on the Van Hoof effect which occurs between the metallic lines FeIλ4920.509 Å and FeIIλ4923.921 Å in RR Lyr. |
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ISSN: | 2213-1337 2213-1345 |
DOI: | 10.1016/j.ascom.2023.100708 |