Jul 6 – 8, 2021
Europe/Zurich timezone

Via Machinae

Jul 8, 2021, 9:00 PM
20m

Speaker

Matthew Buckley (Rutgers University)

Description

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)

Co-authors

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

Presentation materials