Identifying stellar streams in Gaia DR2 with data mining techniques

Summary, in English

Streams of stars from captured dwarf galaxies and dissolved globular clusters are identifiable through the similarity of their orbital parameters, a fact that remains true long after the streams have dispersed spatially. We calculate the integrals of motion for 31 234 stars, to a distance of 4 kpc from the Sun, which have full and accurate 6D phase space positions in the Gaia DR2 catalogue. We then apply a novel combination of data mining, numerical, and statistical techniques to search for stellar streams. This process returns five high confidence streams (including one which was previously undiscovered), all of which display tight clustering in the integral of motion space. Colour–magnitude diagrams indicate that these streams are relatively simple, old, metal-poor populations. One of these resolved streams shares very similar kinematics and metallicity characteristics with the Gaia-Enceladus dwarf galaxy remnant, but with a slightly younger age. The success of this project demonstrates the usefulness of data mining techniques in exploring large data sets.

• Author: Nicholas Borsato; Sarah L. Martell; Jeffrey Simpson
• Publishing year: 2019-12-19
• Language: English
• Pages: 1370-1384
• Publication/Series: Monthly Notices of the Royal Astronomical Society
• Volume: 492
• Issue: 1
• Links: http://dx.doi.org/10.1093/mnras/stz3479
• Document type: Journal article
• Publisher: Oxford University Press
• Topic: Astronomy, Astrophysics and Cosmology
• Keywords: methods: data analysis; Galaxy: kinematics and dynamics; Galaxy: structure
• Status: Published
• ISBN/ISSN/Other: ISSN: 1365-2966