Bibcode
Bittner, A.; Falcón-Barroso, J.; Nedelchev, B.; Dorta, A.; Gadotti, D. A.; Sarzi, M.; Molaeinezhad, A.; Iodice, E.; Rosado-Belza, D.; de Lorenzo-Cáceres, A.; Fragkoudi, F.; Galán-de Anta, P. M.; Husemann, B.; Méndez-Abreu, J.; Neumann, J.; Pinna, F.; Querejeta, M.; Sánchez-Blázquez, P.; Seidel, M. K.
Bibliographical reference
Astronomy and Astrophysics, Volume 628, id.A117, 14 pp.
Advertised on:
8
2019
Journal
Citations
75
Refereed citations
70
Description
We present a convenient, all-in-one framework for the scientific
analysis of fully reduced, (integral-field) spectroscopic data. The
Galaxy IFU Spectroscopy Tool (GIST) is entirely written in Python 3 and
conducts all the steps from the preparation of input data to the
scientific analysis and to the production of publication-quality plots.
In its basic set-up, it extracts stellar kinematics, performs an
emission-line analysis, and derives stellar population properties from
full spectral fitting and via the measurement of absorption
line-strength indices by exploiting the well-known pPXF and GandALF
routines, where the latter has now been implemented in Python. The
pipeline is not specific to any instrument or analysis technique and
provides easy means of modification and further development, thanks to
its modular code architecture. An elaborate, Python-native
parallelisation is implemented and tested on various machines. The
software further features a dedicated visualisation routine with a
sophisticated graphical user interface. This allows an easy, fully
interactive plotting of all measurements, spectra, fits, and residuals,
as well as star formation histories and the weight distribution of the
models. The pipeline has been successfully applied to both low- and
high-redshift data from MUSE, PPAK (CALIFA), and SINFONI, and to
simulated data for HARMONI and WEAVE and is currently being used by the
TIMER, Fornax3D, and PHANGS collaborations. We demonstrate its
capabilities by applying it to MUSE TIMER observations of NGC 1433.
http://ascl.net/1907.025, http://https://abittner.gitlab.io/thegistpipeline
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