Overview

MaNGA

MaNGA (Mapping Nearby Galaxies with APO) is a SDSS-IV survey to understand the physical processes that govern the lifecycle of galaxies. MaNGA is obtaining integral field spectroscopy of 10,000 galaxies at ~kpc spatial scales to probe their gas-phase and stellar properties as a function of location. MaNGA produces 3-D data cubes (with two spatial dimensions and one spectral dimension), and 2-D maps of derived properties. This wealth of spectral information with known spatial inter-connectedness is a powerful tool for unraveling the mysteries of galaxy evolution, but the massive scale of the MaNGA survey severely complicates any attempt to harness the full statistical power of this data set.

Marvin

Marvin is a complete ecosystem designed for overcoming the challenge of searching, accessing, and visualizing the MaNGA data. It consists of a three-pronged approach of a web app, a python package, and an API. The web app, Marvin-web, provides an easily accessible interface for searching the MaNGA data and visual exploration of individual MaNGA galaxies or of the entire sample. The python package, in particular Marvin-tools, allows users to easily and efficiently interact with the MaNGA data via local files, files retrieved from the Science Archive Server, or data directly grabbed from the database. The tools come mainly in the form of convenience functions and classes for interacting with the data. An additional tool is a powerful query functionality that uses the API to query the MaNGA databases and return the search results to your python session. Marvin-API is the critical link that allows Marvin-tools and Marvin-web to interact with the databases, which enables users to harness the statistical power of the MaNGA data set.

Marvin 1.0

Marvin 1.0 began as a pure web app to access, search, view, and comment on MaNGA galaxies. It allowed users to query on global galaxy properties from the sample selection catalog or as determined by the reduction pipeline. Users could download FITS files of the data cubes or the analysis properties. They could view galaxy images, maps, radial gradients, and a subset of the available spectra and spectral fits. Users could then comment on plots or tag galaxies, which was critical for quality assessment of the MaNGA reduction and analysis pipelines. The comments and tags were also searchable to allow users to see assessments made by other team members.

Marvin 1.0 relied on many static aspects, such as downloading FITS files and pre-made png files for the maps, gradients, and spectra. This allowed for fast development, but ultimately limited scalability and interactvity. The Marvin 2.0 web app moves towards a dynamic model that utilizes the spectral and analysis properties databases. Much of the underlying functionality in Marvin-web is helpful for users writing their own analysis software on their own computers, so we packaged these utilities as an easy to use python module (Marvin-tools).