Abstract

Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) is an optical fiber-bundle integral-field unit (IFU) spectroscopic survey that is one of three core programs in the fourth-generation Sloan Digital Sky Survey (SDSS-IV). With a spectral coverage of 3622–10354 Å and an average footprint of ~500 arcsec2 per IFU the scientific data products derived from MaNGA will permit exploration of the internal structure of a statistically large sample of 10,000 low-redshift galaxies in unprecedented detail. Comprising 174 individually pluggable science and calibration IFUs with a near-constant data stream, MaNGA is expected to obtain ~100 million raw-frame spectra and ~10 million reduced galaxy spectra over the six-year lifetime of the survey. In this contribution, we describe the MaNGA Data Reduction Pipeline algorithms and centralized metadata framework that produce sky-subtracted spectrophotometrically calibrated spectra and rectified three-dimensional data cubes that combine individual dithered observations. For the 1390 galaxy data cubes released in Summer 2016 as part of SDSS-IV Data Release 13, we demonstrate that the MaNGA data have nearly Poisson-limited sky subtraction shortward of ~8500 Å and reach a typical 10σ limiting continuum surface brightness μ = 23.5 AB arcsec−2 in a five-arcsecond-diameter aperture in the g-band. The wavelength calibration of the MaNGA data is accurate to 5 km s−1 rms, with a median spatial resolution of 2.54 arcsec FWHM (1.8 kpc at the median redshift of 0.037) and a median spectral resolution of σ = 72 km s−1.

Document Type

Article

Publication Date

9-12-2016

Notes/Citation Information

Published in The Astronomical Journal, v. 152, no. 4, 83, p. 1-35.

© 2016. The American Astronomical Society. All rights reserved.

The copyright holder has granted the permission for posting the article here.

Digital Object Identifier (DOI)

https://doi.org/10.3847/0004-6256/152/4/83

Funding Information

This work was supported by the World Premier International Research Center Initiative (WPI Initiative), MEXT, Japan. A.W. acknowledges support of a Leverhulme Trust Early Career Fellowship. M.A.B. acknowledges support from NSF AST-1517006. G.B. is supported by CONICYT/FONDECYT, Programa de Iniciacion, Folio 11150220. Funding for the Sloan Digital Sky Survey IV has been provided by the Alfred P. Sloan Foundation and the Participating Institutions. SDSS-IV acknowledges support and resources from the Center for High-Performance Computing at the University of Utah.

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