Spitzer Survey of Stellar Structure in Galaxies (S$^4$G). The Pipeline 4: Multi-component decomposition strategies and data release

TL;DR

The paper details the data analysis pipeline for the S$^4$G survey, focusing on multi-component galaxy decompositions using GALFIT, and provides data products and tools for further scientific analysis.

Contribution

It introduces a comprehensive pipeline for multi-component galaxy decomposition, including data preparation, analysis, and public data release, enhancing the reliability of bulge and disk parameter estimates.

Findings

Multi-component models improve bulge parameter accuracy.

Data products and tools are publicly available for community use.

Decomposition strategies are demonstrated with example cases.

Abstract

The Spitzer Survey of Stellar Structure in Galaxies (S$^4$G, Sheth et. al. 2010) is a deep 3.6 and 4.5 $\mu$m imaging survey of 2352 nearby ($< 40$ Mpc) galaxies. We describe the S$^4$G data analysis pipeline 4, which is dedicated to 2-dimensional structural surface brightness decompositions of 3.6 $\mu$m images, using GALFIT3.0 \citep{peng2010}. Besides automatic 1-component S\'ersic fits, and 2-component S\'ersic 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 S\'ersic index and bulge-to-total light ratio ($B/T$), confirming earlier results \citep{laurikainen2007, gadotti2008, weinzirl2009}. In this first paper, 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 ({\bf \tt 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. In the second paper we will present a detailed analysis of the bulge, disk, and bar parameter derived from multi-component decompositions.