Jul 6 – 8, 2021
Europe/Zurich timezone

Via Machinae

Jul 8, 2021, 9:00 PM


Matthew Buckley (Rutgers University)


I describe a new machine learning algorithm, Via Machinae, to identify cold stellar streams in data from the Gaia telescope. Via Machinae is based on ANODE, a general method that uses conditional density estimation and sideband interpolation to detect local overdensities in the data in a model agnostic way. By applying ANODE to the positions, proper motions, and photometry of stars observed by Gaia, Via Machinae obtains a collection of those stars deemed most likely to belong to a stellar stream. In this talk, I will provide an overview of the Via Machinae algorithm, using the known stream GD-1 as a worked example, and show preliminary results of our analysis across the full sky.

Affiliation Rutgers University
Academic Rank Professor

Primary author

Matthew Buckley (Rutgers University)


David Shih (Rutgers University) Lina Necib (California Institute of Technology) John Tamanas (University of California, Santa Cruz)

Presentation materials