On the Fast Track: Rapid construction of stellar stream paths
arXiv:2212.00949 · doi:10.1093/mnras/stad1166
Abstract
Stellar streams are sensitive probes of the Galactic potential. The likelihood of a stream model given stream data is often assessed using simulations. However, comparing to simulations is challenging when even the stream paths can be hard to quantify. Here we present a novel application of Self-Organizing Maps and first-order Kalman Filters to reconstruct a stream's path, propagating measurement errors and data sparsity into the stream path uncertainty. The technique is Galactic-model independent, non-parametric, and works on phase-wrapped streams. With this technique, we can uniformly analyze and compare data with simulations, enabling both comparison of simulation techniques and ensemble analysis with stream tracks of many stellar streams. Our method is implemented in the public Python package TrackStream, available at https://github.com/nstarman/trackstream.
16 pages, 11 figures, preprint
References in corpus (15)
- The Astropy Project: Sustaining and Growing a Community-oriented Open-source Project and the Latest Major Release (v5.0) of the Core Package
- galpy: A Python Library for Galactic Dynamics
- Gaia EDR3 view on Galactic globular clusters
- "Skinny Milky Way, Please", says Sagittarius
- The shape of the inner Milky Way halo from observations of the Pal 5 and GD-1 stellar streams
- A 22 Degree Tidal Tail for Palomar 5
- Generation of mock tidal streams
- galstreams: A Library of Milky Way Stellar Stream Footprints and Tracks
- Milky Way Mass and Potential Recovery Using Tidal Streams in a Realistic Halo
- A direct measurement of the distance to the Galactic center using the kinematics of bar stars
- Variations in the width, density, and direction of the Palomar 5 tidal tails
- Feeling the pull, a study of natural Galactic accelerometers. II: kinematics and mass of the delicate stellar stream of the Palomar 5 globular cluster
- The structure of accreted stellar streams
- Charting Galactic Accelerations with Stellar Streams and Machine Learning
- The Effect of Dwarf Galaxies on the Tidal Tails of Globular Clusters