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The data analysis pipeline for the SDSS-IV MaNGA IFU Galaxy Survey : overview

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Date
18/11/2019
Author
Westfall, Kyle B.
Cappellari, Michele
Bershady, Matthew A.
Bundy, Kevin
Belfiore, Francesco
Ji, Xihan
Law, David R.
Schaefer, Adam
Shetty, Shravan
Tremonti, Christy A.
Yan, Renbin
Andrews, Brett H.
Brownstein, Joel R.
Cherinka, Brian
Coccato, Lodovico
Drory, Niv
Maraston, Claudia
Parikh, Taniya
Sánchez-Gallego, José R.
Thomas, Daniel
Weijmans, Anne-Marie
Barrera-Ballesteros, Jorge
Du, Cheng
Goddard, Daniel
Li, Niu
Masters, Karen
Ibarra Medel, Héctor Javier
Sánchez, Sebastián F.
Yang, Meng
Zheng, Zheng
Zhou, Shuang
Keywords
Methods: data analysis
Techniques: imaging spectroscopy
Surveys
Galaxies: general
Galaxies: fundamental parameters
QB Astronomy
QC Physics
DAS
Metadata
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Abstract
Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) is acquiring integral-field spectroscopy for the largest sample of galaxies to date. By 2020, the MaNGA Survey - one of three core programs in the fourth-generation Sloan Digital Sky Survey (SDSS-IV) - will have observed a statistically representative sample of 104 galaxies in the local Universe z ∼< 0.15. In addition to a robust data-reduction pipeline (DRP), MaNGA has developed a data-analysis pipeline (DAP) that provides higher-level data products. To accompany the first public release of its code base and data products, we provide an overview of the MaNGA DAP, including its software design, workflow, measurement procedures and algorithms, performance, and output data model. In conjunction with our companion paper Belfiore et al., we also assess the DAP output provided for 4718 observations of 4648 unique galaxies in the recent SDSS Data Release 15 (DR15). These analysis products focus on measurements that are close to the data and require minimal model-based assumptions. Namely, we provide stellar kinematics (velocity andvelocity dispersion), emission-line properties (kinematics, fluxes, and equivalent widths), and spectral indices (e.g., D4000 and the Lick indices). We find that the DAP provides robust measurements and errors for the vast majority (>99%) of analyzed spectra. We summarize assessments of the precision and accuracy of our measurements as a function of signal-to-noise, and provide specific guidance to users regarding the limitations of the data. The MaNGA DAP software is publicly available and we encourage community involvement in its development.
Citation
Westfall , K B , Cappellari , M , Bershady , M A , Bundy , K , Belfiore , F , Ji , X , Law , D R , Schaefer , A , Shetty , S , Tremonti , C A , Yan , R , Andrews , B H , Brownstein , J R , Cherinka , B , Coccato , L , Drory , N , Maraston , C , Parikh , T , Sánchez-Gallego , J R , Thomas , D , Weijmans , A-M , Barrera-Ballesteros , J , Du , C , Goddard , D , Li , N , Masters , K , Ibarra Medel , H J , Sánchez , S F , Yang , M , Zheng , Z & Zhou , S 2019 , ' The data analysis pipeline for the SDSS-IV MaNGA IFU Galaxy Survey : overview ' , Astronomical Journal , vol. 158 , no. 6 , 231 . https://doi.org/10.3847/1538-3881/ab44a2
Publication
Astronomical Journal
Status
Peer reviewed
DOI
https://doi.org/10.3847/1538-3881/ab44a2
ISSN
0004-6256
Type
Journal article
Rights
Copyright © 2019 American Astronomical Society. This work has been made available online in accordance with publisher policies or with permission. Permission for further reuse of this content should be sought from the publisher or the rights holder. This is the final published version of the work, which was originally published at https://doi.org/10.3847/1538-3881/ab44a2
Collections
  • University of St Andrews Research
URL
http://adsabs.harvard.edu/abs/2019arXiv190100856W
URI
http://hdl.handle.net/10023/18900

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