The Invisibles: A Detection Algorithm to Trace the Faintest Milky Way Satellites

TL;DR

This paper introduces a specialized data mining algorithm that systematically detects extremely faint Milky Way satellite galaxies using wide-field photometry data, successfully recovering known satellites and identifying new overdensities.

Contribution

The paper presents a novel detection algorithm calibrated with SDSS data that enhances the search for ultra-faint satellite galaxies in the Milky Way halo.

Findings

Successfully recovered all recent SDSS-detected MW satellites

Identified 30 new point source overdensities with no cataloged counterparts

Quantified detection efficiency across various galaxy parameters

Abstract

[Abridged] A specialized data mining algorithm has been developed using wide-field photometry catalogues, enabling systematic and efficient searches for resolved, extremely low surface brightness satellite galaxies in the halo of the Milky Way (MW). Tested and calibrated with the Sloan Digital Sky Survey Data Release 6 (SDSS-DR6) we recover all fifteen MW satellites recently detected in SDSS, six known MW/Local Group dSphs in the SDSS footprint, and 19 previously known globular and open clusters. In addition, 30 point source overdensities have been found that correspond to no cataloged objects. The detection efficiencies of the algorithm have been carefully quantified by simulating more than three million model satellites embedded in star fields typical of those observed in SDSS, covering a wide range of parameters including galaxy distance, scale-length, luminosity, and Galactic latitude.