pith. sign in

arxiv: 2504.08030 · v1 · pith:4I6AE55Znew · submitted 2025-04-10 · 🌌 astro-ph.GA

ELVES-Dwarf I: Satellites Systems of Eight Isolated Dwarf Galaxies in the Local Volume

classification 🌌 astro-ph.GA
keywords dwarfgalaxiessatellitesatelliteshostisolatedstellarcandidates
0
0 comments X
read the original abstract

The satellite populations of Milky Way--mass systems have been extensively studied, significantly advancing our understanding of galaxy formation and dark matter physics. In contrast, the satellites of lower-mass dwarf galaxies remain largely unexplored, despite hierarchical structure formation predicting that dwarf galaxies should host their own satellites. We present the first results of the ELVES-Dwarf survey, which aims to statistically characterize the satellite populations of isolated dwarf galaxies in the Local Volume ($4<D<10$~Mpc). We identify satellite candidates in integrated light using the Legacy Surveys data and are complete down to $M_g\approx -9$ mag. We then confirm the association of satellite candidates with host galaxies using surface brightness fluctuation distances measured from the Hyper Suprime-Cam data. We surveyed 8 isolated dwarf galaxies with stellar masses ranging from sub-Small Magellanic Cloud to Large Magellanic Cloud scales ($10^{7.8} < M_\star^{\rm host}<10^{9.5}\, M_\odot$) and confirmed 6 satellites with stellar masses between $10^{5.6}$ and $10^{8} \, M_\odot$. Most confirmed satellites are star-forming, contrasting with the primarily quiescent satellites observed around Milky Way--mass hosts. By comparing observed satellite abundances and stellar mass functions with theoretical predictions, we find no evidence of a "missing satellite problem" in the dwarf galaxy regime.

This paper has not been read by Pith yet.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Hyrax: An Extensible Framework for Rapid ML Experimentation and Unsupervised Discovery in the Era of Rubin, Roman, and Euclid

    astro-ph.IM 2026-05 unverdicted novelty 5.0

    Hyrax is a GPU-enabled open-source framework for the full ML lifecycle in astronomy, with demonstrations of unsupervised discovery and classification on real survey data from Rubin, ZTF, and other projects.