The Luminosity Function of the Milky Way Satellites
By Sergey E. Koposov, V. Belokurov, N. Evans II, Paul Hewett, M. Irwin, G. Gilmore, D. Zucker, Hans-Walter Rix, M. Fellhauer, Eric F. Bell and 9 more. 2007
311 citations recorded by the source corpus.
We quantify the detectability of stellar Milky Way satellites in the Sloan Digital Sky Survey (SDSS) Data Release 5. We show that the effective search volumes for the recently discovered SDSS satellites depend strongly on their luminosity, with their maximum distance, Dmax, substantially smaller than the Milky Way halo’s virial radius. Calculating the maximum accessible volume, Vmax, for all faint detected satellites allows the calculation of the luminosity function for Milky Way satellite galaxies, accounting quantitatively for their detectability. We find that the number density of satellite galaxies continues to rise toward low luminosities, but may flatten at MV ∼ − 5; within the uncertainties, the luminosity function can be described by a single power law , spanning luminosities from MV = − 2 all the way to the luminosity of the Large Magellanic Cloud. In comparing these results to several semianalytic galaxy formation models, we find that their predictions differ significantly from the data: either the shape of the luminosity function or the model's surface brightness distribution does not match.
Subfields: Astronomy and Astrophysics, Electrical and Electronic Engineering, Instrumentation
View Paper: https://www.semanticscholar.org/paper/3cfb57f306a1975dbe432260bfcb79d45967e13f
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In Astronomy and Astrophysics
- P. Hopkins
- Volker Springel
- Simon D. M. White
- L. Hernquist
- James S. Bullock
- M. Boylan-Kolchin
- A. Benson
- R. Somerville
In Electrical and Electronic Engineering
- James S. Bullock
- Simon D. M. White
- M. Boylan-Kolchin
- Risa Wechsler
- Cheng Li
- K. Johnston
- Qi Guo
- C. Casey
In Instrumentation
- Simon D. M. White
- Volker Springel
- P. Hopkins
- L. Hernquist
- James S. Bullock
- A. Benson
- M. Boylan-Kolchin
- Carlos S. Frenk
Citations in the corpus
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- Mining for Dark Matter Substructure: Inferring Subhalo Population Properties from Strong Lenses with Machine Learning (2019, background): “While the detection of ultrafaint dwarf galaxies through the study of stellar overdensities and kinematics (Koposov et al. 2008, 2015; Bechtol et al. 2015; Drlica-Wagner et al. 2015) can be used to make statements about the underlying dark matter properties, theoretical uncertainties in the…”
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- The discovery of Segue 2: a prototype of the population of satellites of satellites (2009, background): “In the next panel, the density of resolved stars is shown, and now there is an evident overdensity with significance (Koposov et al. 2008)S = 4.7 at the centre of the image.”
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