University of Oulu

D J Prole, M Hilker, R F J van der Burg, M Cantiello, A Venhola, E Iodice, G van de Ven, C Wittmann, R F Peletier, S Mieske, M Capaccioli, N R Napolitano, M Paolillo, M Spavone, E Valentijn, Halo mass estimates from the globular cluster populations of 175 low surface brightness galaxies in the Fornax cluster, Monthly Notices of the Royal Astronomical Society, Volume 484, Issue 4, April 2019, Pages 4865–4880,

Halo mass estimates from the globular cluster populations of 175 low surface brightness galaxies in the Fornax cluster

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Author: Prole, D. J.1,2; Hilker, M.1; van der Burg, R. F. J.1;
Organizations: 1European Southern Observatory, Karl-Schwarzschild-Str 2, D-85748 Garching bei München, Germany
2School of Physics and Astronomy, Cardiff University, The Parade, Cardiff CF243AA, UK
3INAF-Osservatorio Astronomico d’Abruzzo, Via M. Maggini snc, I-64100 Teramo, Italy
4Division of Astronomy, Department of Physics, University of Oulu, FI-90014 Oulu, Finland
5INAF-Astronomical Observatory of Capodimonte, via Moiariello 16, I-80131 Naples, Italy
6Astronomisches Rechen-Institut, Zentrum f ̈ur Astronomie der Universität Heidelberg, Mönchhofstraße 12-14, D-69120 Heidelberg, Germany
7Kapteyn Astronomical Institute, University of Groningen, PO Box 72, NL-9700 AV Groningen, the Netherlands
8European Southern Observatory, Alonso de Cordova 3107, Vitacura, Chile
9University of Naples “Federico II”, C.U. Monte Sant’Angelo, Via Cinthia, I-80126 Naples, Italy
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 4.8 MB)
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Language: English
Published: Oxford University Press, 2019
Publish Date: 2020-02-13


The halo masses Mhalo of low surface brightness (LSB) galaxies are critical measurements for understanding their formation processes. One promising method to estimate a galaxy’s Mhalo is to exploit the empirical scaling relation between Mhalo and the number of associated globular clusters (NGC). We use a Bayesian mixture model approach to measure NGC for 175 LSB [23 ≤〈μe,r〉(mag arcsec−2) ≤ 28] galaxies in the Fornax cluster using the Fornax Deep Survey data; this is the largest sample of low-mass galaxies so-far analysed for this kind of study. The proximity of the Fornax cluster means that we can measure galaxies with much smaller physical sizes [0.3 ≤ re,r (kpc) ≤ 9.5] compared to previous studies of the GC systems of LSB galaxies, probing stellar masses down to M* ∼ 105 M⊙. The sample also includes 12 ultra-diffuse galaxies (UDGs), with projected r-band half-light radii greater than 1.5 kpc. Our results are consistent with an extrapolation of the M*−Mhalo relation predicted from abundance matching. In particular, our UDG measurements are consistent with dwarf-sized haloes, having typical masses between 1010 and 1011 M⊙. Overall, our UDG sample is statistically indistinguishable from smaller LSB galaxies in the same magnitude range. We do not find any candidates likely to be as rich as some of those found in the Coma cluster. We suggest that environment might play a role in producing GC-rich LSB galaxies.

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Series: Monthly notices of the Royal Astronomical Society
ISSN: 0035-8711
ISSN-E: 1365-8711
ISSN-L: 0035-8711
Volume: 484
Issue: 4
Pages: 4865 - 4880
DOI: 10.1093/mnras/stz326
Type of Publication: A1 Journal article – refereed
Field of Science: 115 Astronomy and space science
Funding: CW is supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) through project 394551440. GvdV acknowledges funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 724857 (Consolidator Grant ArcheoDyn). AV would like to thank the Vilho, Yrjö, and Kalle Väisälä Foundation of the Finnish Academy of Science and Letters for the financial support. RFP and AV acknowledge financial support from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodovska-Curie grant agreement no. 721463 to the SUNDIAL ITN network.
EU Grant Number: (721463) SUNDIAL - SUrvey Network for Deep Imaging Analysis and Learning
Copyright information: © 2019 The Author(s). Published by Oxford University Press on behalf of the Royal Astronomical Society. All Rights Reserved.