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|Title:||P-MaNGA: full spectral fitting and stellar population maps from prototype observations||Authors:||Wilkinson, David M.
BELFIORE, FRANCESCO MICHEL CONCETTO
|Issue Date:||2015||Journal:||MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY||Number:||449||Issue:||1||First Page:||328||Abstract:||MaNGA (Mapping Nearby Galaxies at Apache Point Observatory) is a 6-yr SDSS-IV (Sloan Digital Sky Survey IV) survey that will obtain resolved spectroscopy from 3600 to 10 300 Å for a representative sample of over 10 000 nearby galaxies. In this paper, we derive spatially resolved stellar population properties and radial gradients by performing full spectral fitting of observed galaxy spectra from P-MaNGA, a prototype of the MaNGA instrument. These data include spectra for 18 galaxies, covering a large range of morphological type. We derive age, metallicity, dust, and stellar mass maps, and their radial gradients, using high spectral-resolution stellar population models, and assess the impact of varying the stellar library input to the models. We introduce a method to determine dust extinction which is able to give smooth stellar mass maps even in cases of high and spatially non-uniform dust attenuation. With the spectral fitting, we produce detailed maps of stellar population properties which allow us to identify galactic features among this diverse sample such as spiral structure, smooth radial profiles with little azimuthal structure in spheroidal galaxies, and spatially distinct galaxy sub-components. In agreement with the literature, we find the gradients for galaxies identified as early type to be on average flat in age, and negative (-0.15 dex/R<SUB>e</SUB>) in metallicity, whereas the gradients for late-type galaxies are on average negative in age (-0.39 dex/R<SUB>e</SUB>) and flat in metallicity. We demonstrate how different levels of data quality change the precision with which radial gradients can be measured. We show how this analysis, extended to the large numbers of MaNGA galaxies, will have the potential to shed light on galaxy structure and evolution.||Acknowledgments:||Funding for SDSS-III and SDSS-IV has been provided by the Alfred P. Sloan Foundation and Participating Institutions. Additional funding for SDSS-III comes from the National Science Foundation and the US Department of Energy Office of Science. Further information about both projects is available at www.sdss3.org . SDSS is managed by the Astrophysical Research Consortium for the Participating Institutions in both collaborations. In SDSS-III, these include the University of Arizona, the Brazilian Participation Group, Brookhaven National Laboratory, Carnegie Mellon University, University of Florida, the French Participation Group, the German Participation Group, Harvard University, the Instituto de Astrofisica de Canarias, the Michigan State/Notre Dame/JINA Participation Group, Johns Hopkins University, Lawrence Berkeley National Laboratory, Max Planck Institute for Astrophysics, Max Planck Institute for Extraterrestrial Physics, New Mexico State University, New York University, Ohio State University, Pennsylvania State University, University of Portsmouth, Princeton University, the Spanish Participation Group, University of Tokyo, University of Utah, Vanderbilt University, University of Virginia, University of Washington, and Yale University. The Participating Institutions in SDSS-IV are Carnegie Mellon University, Colorado University, Boulder, Harvard–Smithsonian Center for Astrophysics Participation Group, Johns Hopkins University, Kavli Institute for the Physics and Mathematics of the Universe Max-Planck-Institut fuer Astrophysik (MPA Garching), Max-Planck-Institut fuer Extraterrestrische Physik (MPE), Max-Planck-Institut fuer Astronomie (MPIA Heidelberg), National Astronomical Observatory of China, New Mexico State University, New York University, The Ohio State University, Penn State University, Shanghai Astronomical Observatory, United Kingdom Participation Group, University of Portsmouth, University of Utah, University of Wisconsin, and Yale University. The authors would like to thank Sebastian F. Sanchez for his very useful and detailed comments and to Roberto Cid Fernandes for providing access to the CALIFA data used in Fig. 16 . Numerical computations were done on the Sciama High Performance Compute (HPC) cluster which is supported by the ICG, SEPNet, and the University of Portsmouth. MC acknowledges support from a Royal Society University Research Fellowship.||URI:||http://hdl.handle.net/20.500.12386/29571||URL:||https://academic.oup.com/mnras/article/449/1/328/1317763||ISSN:||0035-8711||DOI:||10.1093/mnras/stv301||Bibcode ADS:||2015MNRAS.449..328W||Fulltext:||open|
|Appears in Collections:||1.01 Articoli in rivista|
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checked on Jan 19, 2021
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