Marvin: A Tool Kit for Streamlined Access and Visualization of the SDSS-IV MaNGA Data Set

Abstract

The Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey, one of three core programs of the fourth-generation Sloan Digital Sky Survey (SDSS-IV), is producing a massive, highdimensional integral field spectroscopic data set. However, leveraging the MaNGA data set to address key questions about galaxy formation presents serious data-related challenges due to the combination of its spatially inter-connected measurements and sheer volume. For each galaxy, the MaNGA pipelines produce relatively large data files to preserve the spatial correlations of the spectra and measurements, but this comes at the expense of storing the data set in a coarsely-chunked manner. The coarse chunking and total volume of the data make it time-consuming to download and curate locally-stored data. Thus, accessing, querying, visually exploring, and performing statistical analyses across the whole data set at a fine-grained scale is extremely challenging using just FITS files. To overcome these challenges, we have developed Marvin: a toolkit consisting of a Python package, Application Programming Interface (API), and web application utilizing a remote database. Marvin's robust and sustainable design minimizes maintenance, while facilitating user-contributed extensions such as high level analysis code. Finally, we are in the process of abstracting out Marvin's core functionality into a separate product so that it can serve as a foundation for others to develop Marvin-like systems for new science applications.

Signatures of Stellar Accretion in MaNGA Early-type Galaxies

“…De-projected distances and stellar kinematic maps have been calculated by the MaNGA Data Analysis Pipeline (DAP; Westfall et al 2019). This work also makes use of Marvin (Cherinka et al 2017), the specially designed tool for access and handling of MaNGA data 1 . This paper is based on the SDSS Data Release 15 (DR15), which consists of the observations of the first 4675 MaNGA targets.…”

SDSS-IV MaNGA: spatially resolved star formation histories and the connection to galaxy physical properties

“…Funding for the Sloan Digital Sky Survey IV has been provided by the Alfred P. Sloan Foundation, the U.S. Department of Energy Office of Science, and the Participating Institutions. SDSS acknowledges support and resources from the centre for High- Performance (Cherinka et al 2017). This research has made use of PYQZ (Dopita et al 2013), a Python module to derive the ionization parameter and oxygen abundance of HII regions from their strong emission line ratios hosted at http://fpavogt.github.io/pyqz.…”

SDSS-IV MaNGA: identification of active galactic nuclei in optical integral field unit surveys

“…The main output products of the Data Analysis Pipeline then include the stellar absorption line kinematics (stellar velocity and stellar velocity dispersion measurements) and emission line measurements of 21 major optical emission lines in the MaNGA spectral range. Both non-parametric parameters (emission line flux, equivalent width) and Gaussian-profile measurements (emission line flux, velocity, velocity dispersion) are provided (see also Cherinka et al 2017). We note that the Gaussian profile velocity dispersion σ line still needs to be corrected for the instrumental dispersion σ inst at the fitted line center by the user through σ line,corr = σ 2 line − σ 2 inst .…”