Publication: The spitzer survey of stellar structure in galaxies (S^4G): multi-component decomposition strategies and data release
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2015-07
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University Chicago Press
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The Spitzer Survey of Stellar Structure in Galaxies (S^4G) is a deep 3.6 and 4.5 μm imaging survey of 2352 nearby (<40 Mpc) galaxies. We describe the S(^4)G 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 Sersic fits, and 2-component Sersic 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 Sersic 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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© 2015. The American Astronomical Society.
Artículo firmado por 22 autores.
H.S., E.L., and S.C. acknowledge the Academy of Finland for support. J.L. was supported by the Vaisala Foundation Grant. E.A. and A.B. acknowledge the CNES (Centre National d'Etudies Spatiales-France) for financial support. The authors also acknowledge support from the FP7 Marie Curie Actions of the European Commission, via the Initial Training Network DAGAL under REA grant agreement number 289313.
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