The Spitzer Survey of Stellar Structure in Galaxies (S4G): Multi-component Decomposition Strategies and Data Release

Salo, H.; Laurikainen, Eija; Laine, Jarkko; Comerón, Sebastien; Gadotti, Dimitri A.; Buta, Ron; Sheth, Kartik; Zaritsky, Dennis; Ho, Luis; Knapen, J. H.; Athanassoula, E.; Bosma, Albert; Laine, Seppo; Cisternas, M.; Kim, Taehyun; Muñoz-Mateos, Juan Carlos; Regan, Michael; Hinz, Joannah L.; Gil de Paz, Armando; Menendez-Delmestre, Karin; Mizusawa, Trisha; Erroz-Ferrer, S.; Meidt, Sharon E.; Querejeta, Miguel
Referencia bibliográfica

The Astrophysical Journal Supplement Series, Volume 219, Issue 1, article id. 4, 45 pp. (2015).

Fecha de publicación:
7
2015
Número de autores
24
Número de autores del IAC
3
Número de citas
232
Número de citas referidas
211
Descripción
The Spitzer Survey of Stellar Structure in Galaxies (S4G) is a deep 3.6 and 4.5 μm imaging survey of 2352 nearby (<40 Mpc) galaxies. We describe the S4G data analysis pipeline 4, which is dedicated to two-dimensional structural surface brightness decompositions of 3.6 μm images, using GALFIT3.0. Besides automatic 1-component Sérsic fits, and 2-component Sérsic bulge + exponential disk fits, we present human-supervised multi-component decompositions, which include, when judged appropriate, a central point source, bulge, disk, and bar components. Comparison of the fitted parameters indicates that multi-component models are needed to obtain reliable estimates for the bulge Sérsic index and bulge-to-total light ratio (B/T), confirming earlier results. Here, we describe the preparations of input data done for decompositions, give examples of our decomposition strategy, and describe the data products released via IRSA and via our web page (www.oulu.fi/astronomy/S4G_PIPELINE4/MAIN). These products include all the input data and decomposition files in electronic form, making it easy to extend the decompositions to suit specific science purposes. We also provide our IDL-based visualization tools (GALFIDL) developed for displaying/running GALFIT-decompositions, as well as our mask editing procedure (MASK_EDIT) used in data preparation. A detailed analysis of the bulge, disk, and bar parameters derived from multi-component decompositions will be published separately.
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