The Hough Stream Spotter: A New Method for Detecting Linear Structure in Resolved Stars and Application to the Stellar Halo of M31

TL;DR

The paper introduces the Hough Stream Spotter (HSS), a novel method for detecting linear stellar streams in galaxy halos, demonstrated on M31 data, with potential for future space telescope applications to study dark matter.

Contribution

The HSS algorithm is a new tool that successfully detects globular cluster streams in external galaxies, expanding the scope of stellar stream studies beyond the Milky Way.

Findings

Successfully rediscovered known dwarf streams in M31

Identified 27 new linear GC stream-like structures in M31

Most significant detections show strong red giant branch signals in CMDs

Abstract

Stellar streams from globular clusters (GCs) offer constraints on the nature of dark matter and have been used to explore the dark matter halo structure and substructure of our Galaxy. Detection of GC streams in other galaxies would broaden this endeavor to a cosmological context, yet no such streams have been detected to date. To enable such exploration, we develop the Hough Stream Spotter (HSS), and apply it to the Pan-Andromeda Archaeological Survey (PAndAS) photometric data of resolved stars in M31's stellar halo. We first demonstrate that our code can re-discover known dwarf streams in M31. We then use the HSS to blindly identify 27 linear GC stream-like structures in the PAndAS data. For each HSS GC stream candidate, we investigate the morphologies of the streams and the colors and magnitudes of all stars in the candidate streams. We find that the five most significant detections show a stronger signal along the red giant branch in color-magnitude diagrams (CMDs) than spurious non-stream detections. Lastly, we demonstrate that the HSS will easily detect globular cluster streams in future Nancy Grace Roman Space Telescope data of nearby galaxies. This has the potential to open up a new discovery space for GC stream studies, GC stream gap searches, and for GC stream-based constraints on the nature of dark matter.