The Milky Way Project: Mapping star formation in our home Galaxy, one click at a time
Abstract
In the recent years, citizen science has helped astronomers comb through large data sets to identify patterns and objects that are not easily found through automated processes. The Milky Way Project (MWP), a popular citizen science initiative, presents internet users with images from the GLIMPSE, MIPSGAL, SMOG and CYGNUS-X surveys of the Galactic plane using the Spitzer Space Telescope. These citizen scientists are directed to make "classification" drawings on the images to identify targeted classes of astronomical objects. We present an updated data reduction pipeline for the MWP. Written from the ground up in Python, this data reduction pipeline allows for the aggregation of classifications made by MWP users into catalogs of infrared (IR) bubbles, IR bow shocks and “yellowballs” (which may be the early precursors of IR bubbles). Coupled with the more accurate bubble classification tool used in the latest iterations of the MWP, this pipeline enables for better accuracy in the shapes and sizes of the bubbles when compared with those listed in the first MWP data release (DR1). We obtain an initial catalog of over 4000 bubbles using 2 million user classifications made between 2012 and 2015. Combined with the classifications from the latest MWP iteration (2016-2017), we will use a database of over 4 million classifications to produce a MWP DR2 bubble catalog. We will also create the first catalog of candidate IR bow shocks identified through citizen science and an updated “yellowball” catalog. This work is supported by the National Science Foundation under grants CAREER-1454334 and AST-1411851.
- Publication:
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American Astronomical Society Meeting Abstracts #229
- Pub Date:
- January 2017
- Bibcode:
- 2017AAS...22934008J