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The data analysis pipeline for the SDSS-IV MaNGA IFU Galaxy Survey : overview
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dc.contributor.author | Westfall, Kyle B. | |
dc.contributor.author | Cappellari, Michele | |
dc.contributor.author | Bershady, Matthew A. | |
dc.contributor.author | Bundy, Kevin | |
dc.contributor.author | Belfiore, Francesco | |
dc.contributor.author | Ji, Xihan | |
dc.contributor.author | Law, David R. | |
dc.contributor.author | Schaefer, Adam | |
dc.contributor.author | Shetty, Shravan | |
dc.contributor.author | Tremonti, Christy A. | |
dc.contributor.author | Yan, Renbin | |
dc.contributor.author | Andrews, Brett H. | |
dc.contributor.author | Brownstein, Joel R. | |
dc.contributor.author | Cherinka, Brian | |
dc.contributor.author | Coccato, Lodovico | |
dc.contributor.author | Drory, Niv | |
dc.contributor.author | Maraston, Claudia | |
dc.contributor.author | Parikh, Taniya | |
dc.contributor.author | Sánchez-Gallego, José R. | |
dc.contributor.author | Thomas, Daniel | |
dc.contributor.author | Weijmans, Anne-Marie | |
dc.contributor.author | Barrera-Ballesteros, Jorge | |
dc.contributor.author | Du, Cheng | |
dc.contributor.author | Goddard, Daniel | |
dc.contributor.author | Li, Niu | |
dc.contributor.author | Masters, Karen | |
dc.contributor.author | Ibarra Medel, Héctor Javier | |
dc.contributor.author | Sánchez, Sebastián F. | |
dc.contributor.author | Yang, Meng | |
dc.contributor.author | Zheng, Zheng | |
dc.contributor.author | Zhou, Shuang | |
dc.date.accessioned | 2019-11-12T13:30:01Z | |
dc.date.available | 2019-11-12T13:30:01Z | |
dc.date.issued | 2019-11-18 | |
dc.identifier.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 | en |
dc.identifier.issn | 0004-6256 | |
dc.identifier.other | PURE: 262929038 | |
dc.identifier.other | PURE UUID: 79e5285f-7835-498f-9966-2238853e2903 | |
dc.identifier.other | BibCode: 2019arXiv190100856W | |
dc.identifier.other | ORCID: /0000-0002-5908-6852/work/66398405 | |
dc.identifier.other | WOS: 000499383400001 | |
dc.identifier.other | Scopus: 85081203494 | |
dc.identifier.uri | https://hdl.handle.net/10023/18900 | |
dc.description.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. | |
dc.language.iso | eng | |
dc.relation.ispartof | Astronomical Journal | en |
dc.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 | en |
dc.subject | Methods: data analysis | en |
dc.subject | Techniques: imaging spectroscopy | en |
dc.subject | Surveys | en |
dc.subject | Galaxies: general | en |
dc.subject | Galaxies: fundamental parameters | en |
dc.subject | QB Astronomy | en |
dc.subject | QC Physics | en |
dc.subject | DAS | en |
dc.subject.lcc | QB | en |
dc.subject.lcc | QC | en |
dc.title | The data analysis pipeline for the SDSS-IV MaNGA IFU Galaxy Survey : overview | en |
dc.type | Journal article | en |
dc.contributor.sponsor | The Leverhulme Trust | en |
dc.description.version | Postprint | en |
dc.contributor.institution | University of St Andrews. School of Physics and Astronomy | en |
dc.contributor.institution | University of St Andrews. Centre for Contemporary Art | en |
dc.identifier.doi | https://doi.org/10.3847/1538-3881/ab44a2 | |
dc.description.status | Peer reviewed | en |
dc.identifier.url | http://adsabs.harvard.edu/abs/2019arXiv190100856W | en |
dc.identifier.grantnumber | ECF-2014-767 | en |
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