We describe the Sloan

The fourth generation of the Sloan

The tight correlation between total galaxy stellar mass and star formation rate (SFR) has become known as the star forming main sequence. Using ∼ 487,000 spaxels from galaxies observed as part of the Sloan Digital Sky Survey Mapping Galaxies at Apache Point Observatory (MaNGA) survey, we confirm previous results that a correlation also exists between the surface densities of star formation (Σ SFR ) and stellar mass (Σ ) on kpc scales, representing a 'resolved' main sequence. Using a new metric (∆Σ SFR ), which measures the relative enhancement or deficit of star formation on a spaxel-by-spaxel basis relative to the resolved main sequence, we investigate the SFR profiles of 864 galaxies as a function of their position relative to the global star forming main sequence (∆SFR). For galaxies above the global main sequence (positive ∆SFR) ∆Σ SFR is elevated throughout the galaxy, but the greatest enhancement in star formation occurs at small radii (< 3 kpc, or 0.5 R e ). Moreover, galaxies that are at least a factor of three above the main sequence show diluted gas phase metallicities out to 2 R e , indicative of metal-poor gas inflows accompanying the starbursts. For quiescent/passive galaxies that lie at least a factor of 10 below the star forming main sequence there is an analogous deficit of star formation throughout the galaxy with the lowest values of ∆Σ SFR in the central 3 kpc. Our results are in qualitative agreement with the 'compaction' scenario in which a central starburst leads to mass growth in the bulge and may ultimately precede galactic quenching from the inside-out.

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The Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey is currently acquiring integral-field spectroscopy for the largest sample of galaxies to date. By 2020, the MaNGA Survey—which is 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 and velocity 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. We also 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.