DELVE Milky Way Satellite Galaxy Census. I. Satellite Population and Survey Selection Function in DES, DELVE, and Pan-STARRS

Tan, C. Y.; Drlica-Wagner, A.; Pace, A. B.; Cerny, W.; Nadler, E. O.; Doliva-Dolinsky, A.; Anbajagane, D.; Li, T. S.; Simon, J. D.; Vivas, A. K.; Walker, A. R.; Adamów, M.; Bechtol, K.; Carlin, J. L.; Casey, Q. O.; Chang, C.; Chaturvedi, A.; Cheng, T.-Y.; Chiti, A.; Choi, Y.; Crnojević, D.; Ferguson, P. S.; Gruendl, R. A.; Ji, A. P.; Limberg, G.; Medina, G. E.; Mutlu-Pakdil, B.; Noël, N. E. D.; Overdeck, K.; Placco, V. M.; Riley, A. H.; Sand, D. J.; Sharp, J.; Sherman, N. F.; Stringfellow, G. S.; Wechsler, R. H.; Aguena, M.; Allam, S.; Alves, O.; Bacon, D.; Brooks, D.; Burke, D. L.; Camilleri, R.; Carballo-Bello, J. A.; Carnero Rosell, A.; Carretero, J.; da Costa, L. N.; da Silva Pereira, M. E.; Davis, T. M.; De Vicente, J.; Desai, S.; Everett, S.; Flaugher, B.; Frieman, J.; García-Bellido, J.; Gruen, D.; Gutierrez, G.; Herner, K.; Hinton, S. R.; Hollowood, D. L.; James, D. J.; Kuehn, K.; Lahav, O.; Lee, S.; Marshall, J. L.; Martínez-Vázquez, C. E.; Massana, P.; Mena-Fernández, J.; Miquel, R.; Muir, J.; Myles, J.; Ogando, R. L. C.; Plazas Malagón, A. A.; Porredon, A.; Sanchez, E.; Cid, D. Sanchez; Sevilla-Noarbe, I.; Smith, M.; Suchyta, E.; Swanson, M. E. C.; To, C.; Tollerud, E. J.; Tucker, D. L.; Vikram, V.; Weaverdyck, N.; Yamamoto, M.; Zenteno, A.; DELVE Collaboration; DES Collaboration

doi:10.3847/1538-4357/ae4479

Published March 20, 2026 | Version Published

Journal Article Open

DELVE Milky Way Satellite Galaxy Census. I. Satellite Population and Survey Selection Function in DES, DELVE, and Pan-STARRS

1. University of Chicago
2. NSF-Simons AI Institute for the Sky (SkAI), 172 E. Chestnut Street, Chicago, IL 60611, USA
3. Fermilab
4. University of Virginia
5. Yale University
6. University of California, San Diego
7. University of Surrey
8. University of Toronto
9. Carnegie Observatories
10. Cerro Tololo Inter-American Observatory
11. National Center for Supercomputing Applications
12. University of Wisconsin–Madison
13. Rubin Observatory/AURA, 950 North Cherry Avenue, Tucson, AZ, 85719, USA
14. Dartmouth College
15. University of Groningen
16. NOIRLab
17. University of Tampa
18. University of Washington
19. University of Illinois Urbana-Champaign
20. Durham University
21. Lund University
22. University of Arizona
23. Boston University
24. University of Colorado Boulder
25. Stanford University
26. SLAC National Accelerator Laboratory
27. Trieste Astronomical Observatory
28. Laboratório Interinstitucional de e-Astronomia
29. University of Michigan–Ann Arbor
30. University of Portsmouth
31. University College London
32. University of Queensland
33. University of Tarapacá
34. Instituto de Astrofísica de Canarias
35. University of La Laguna
36. Institute for High Energy Physics
37. Universität Hamburg
38. Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas
39. Indian Institute of Technology Hyderabad
40. California Institute of Technology
41. Institute for Theoretical Physics
42. Ludwig-Maximilians-Universität München
43. University of California, Santa Cruz
44. ASTRAVEO LLC, P.O. Box 1668, Gloucester, MA 01931, USA
45. Applied Materials (United States)
46. Macquarie University
47. Lowell Observatory
48. Jet Propulsion Lab
49. Texas A&M University
50. International Gemini Observatory/NSF NOIRLab, 670 N. A'ohoku Place, Hilo, HI 96720, USA
51. NSF NOIRLab, Casilla 603, La Serena, Chile
52. French National Centre for Scientific Research
53. Institució Catalana de Recerca i Estudis Avançats
54. University of Cincinnati
55. Perimeter Institute
56. Princeton University
57. Centro de Tecnologia da Informação Renato Archer
58. National Observatory
59. Ruhr University Bochum
60. University of Zurich
61. Lancaster University
62. Oak Ridge National Laboratory
63. Space Telescope Science Institute
64. Central University of Kerala
65. University of California, Berkeley
66. Lawrence Berkeley National Laboratory
67. Duke University

The properties of Milky Way satellite galaxies have important implications for galaxy formation, reionization, and the fundamental physics of dark matter. However, the population of Milky Way satellites includes the faintest known galaxies, and current observations are incomplete. To understand the impact of observational selection effects on the known satellite population, we perform rigorous, quantitative estimates of the Milky Way satellite galaxy detection efficiency in three wide-field survey datasets: the Dark Energy Survey Year 6, the DECam Local Volume Exploration Data Release 3, and the Pan-STARRS1 Data Release 1. Together, these surveys cover ∼13,600 deg² to g ∼ 24.0 and ∼27,700 deg² to g ∼ 22.5, spanning ∼91% of the high-Galactic-latitude sky (∣b∣ ≥ 15°). We apply multiple detection algorithms over the combined footprint and recover 49 known satellites above a strict census detection threshold. To characterize the sensitivity of our census, we run our detection algorithms on a large set of simulated galaxies injected into the survey data, which allows us to develop models that predict the detectability of satellites as a function of their properties. We then fit an empirical model to our data and infer the luminosity function, radial distribution, and size–luminosity relation of Milky Way satellite galaxies. Our empirical model predicts a total of 265⁺⁷⁹₋₄₇ satellite galaxies with −20 ≤ M_V ≤ 0, half-light radii of 15 ≤ r_1/2, (pc) ≤ 3000, and galactocentric distances of 10 ≤ D_GC(kpc) ≤ 300. We also identify a mild anisotropy in the angular distribution of the observed galaxies, at a significance of ∼2σ, which can be attributed to the clustering of satellites associated with the LMC.

Copyright and License

© 2026. The Author(s). Published by the American Astronomical Society. Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.

Acknowledgement

We thank the anonymous referee for providing many useful comments that helped us improve this manuscript. C.Y.T. was supported by the U.S. National Science Foundation (NSF) through the grants AST-2108168 and AST-2307126. W.C. gratefully acknowledges support from a Gruber Science Fellowship at Yale University. This material is based upon work supported by the National Science Foundation Graduate Research Fellowship Program under grant No. DGE2139841. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. A.D.D. acknowledges support from STFC grants ST/Y002857/1. D.J.S. acknowledges support from NSF grant AST-2205863. This research was supported in part by grant NSF PHY-2309135 to the Kavli Institute for Theoretical Physics (KITP).

The DELVE project is partially supported by the NASA Fermi Guest Investigator Program Cycle 9 No. 91201 and by Fermilab LDRD project L2019-011. This material is based upon work supported by the National Science Foundation under grant No. AST-2108168, AST-2108169, AST-2307126, and AST-2407526. This research award is partially funded by a generous gift of Charles Simonyi to the NSF Division of Astronomical Sciences. The award is made in recognition of significant contributions to Rubin Observatory's Legacy Survey of Space and Time.

Funding for the DES Projects has been provided by the U.S. Department of Energy, the U.S. National Science Foundation, the Ministry of Science and Education of Spain, the Science and Technology Facilities Council of the United Kingdom, the Higher Education Funding Council for England, the National Center for Supercomputing Applications at the University of Illinois at Urbana-Champaign, the Kavli Institute of Cosmological Physics at the University of Chicago, the Center for Cosmology and Astro-Particle Physics at the Ohio State University, the Mitchell Institute for Fundamental Physics and Astronomy at Texas A&M University, Financiadora de Estudos e Projetos, Fundaç ao Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro, Conselho Nacional de Desenvolvimento Científico e Tecnológico and the Ministério da Ciência, Tecnologia e Inovaç ao, the Deutsche Forschungsgemeinschaft, and the Collaborating Institutions in the Dark Energy Survey.

The Collaborating Institutions are Argonne National Laboratory, the University of California at Santa Cruz, the University of Cambridge, Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas-Madrid, the University of Chicago, University College London, the DES-Brazil Consortium, the University of Edinburgh, the Eidgenössische Technische Hochschule (ETH) Zürich, Fermi National Accelerator Laboratory, the University of Illinois at Urbana-Champaign, the Institut de Ciències de l’Espai (IEEC/CSIC), the Institut de Física d’Altes Energies, Lawrence Berkeley National Laboratory, the Ludwig-Maximilians Universität München and the associated Excellence Cluster Universe, the University of Michigan, NSF NOIRLab, the University of Nottingham, The Ohio State University, the University of Pennsylvania, the University of Portsmouth, SLAC National Accelerator Laboratory, Stanford University, the University of Sussex, Texas A&M University, and the OzDES Membership Consortium.

Based in part on observations at NSF Cerro Tololo Inter-American Observatory at NSF NOIRLab (NOIRLab Prop. ID 2012B-0001; PI: J. Frieman), which is managed by the Association of Universities for Research in Astronomy (AURA) under a cooperative agreement with the National Science Foundation.

The DES data management system is supported by the National Science Foundation under grant Nos. AST-1138766 and AST-1536171. The DES participants from Spanish institutions are partially supported by MICINN under grants PID2021-123012, PID2021-128989 PID2022-141079, SEV-2016-0588, CEX2020-001058-M, and CEX2020-001007-S, some of which include ERDF funds from the European Union. IFAE is partially funded by the CERCA program of the Generalitat de Catalunya.

We acknowledge support from the Brazilian Instituto Nacional de Ciência e Tecnologia (INCT) do e-Universo (CNPq grant 465376/2014-2).

This document was prepared by the DES Collaboration using the resources of the Fermi National Accelerator Laboratory (Fermilab), a U.S. Department of Energy, Office of Science, Office of High Energy Physics HEP User Facility. Fermilab is managed by Fermi Forward Discovery Group, LLC, acting under contract No. 89243024CSC000002.

Contributions

C.Y.T. performed the main dwarf search, conducted the corresponding analysis, produced all plots and tables in the paper, and led the writing. A.D.W. provided direct supervision for the research and guided the data processing and search algorithms. A.B.P. and W.C. guided major analysis decisions regarding building Tables 1 and 5 as well as thresholds for including satellites in the census. E.O.N. and A.D.D. advised on modeling choices for the empirical model. D.A. helped run balrog for blending simulations. T.S.L., J.D.S., A.K.V., and A.R.W. internally reviewed the paper. The authors from M.A. to R.H.W. contributed to producing and characterizing one or more of the following data products used in the paper: DES Y6 and DELVE DR3 source catalogs, known dwarf galaxy catalogs, and/or provided valuable comments that improved the paper’s clarity and quality. Builders: The remaining authors contributed to this work through the construction of DECam and other aspects of data collection; data processing and calibration; developing widely used methods, codes, and simulations; running pipelines and validation tests; and promoting the science analysis.

Facilities

Blanco - Cerro Tololo Inter-American Observatory's 4 meter Blanco Telescope (DECam), PS1 - Panoramic Survey Telescope and Rapid Response System Telescope #1 (Pan-STARRS), Gaia - , Subaru - Subaru Telescope (HSC).

Software References

astropy (Astropy Collaboration et al. 2013, 2018), emcee (D. Foreman-Mackey et al. 2013), fitsio,⁸³ healpix (K. M. Górski et al. 2005),⁸⁴ healpy (A. Zonca et al. 2019),⁸⁵ healsparse,⁸⁶ matplotlib (J. D. Hunter 2007), numpy (C. R. Harris et al. 2020), simple (K. Bechtol et al. 2015), scipy (P. Virtanen et al. 2020), skymap,⁸⁷ ugali (K. Bechtol et al. 2015; A. Drlica-Wagner et al. 2020).

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Is new version of: Discussion Paper: arXiv:2509.12313 (arXiv)

National Science Foundation
AST-2108168
National Science Foundation
AST-2307126
Yale University
Gruber Science Fellowship -
National Science Foundation
DGE2139841
Science and Technology Facilities Council
ST/Y002857/1
National Science Foundation
AST-2205863
National Science Foundation
PHY-2309135
National Council for Scientific and Technological Development
465376/2014-2
Fermi National Accelerator Laboratory
89243024CSC000002

Submitted: 2025-09-15
Accepted: 2026-01-28
Available: 2026-03-13

Published

Caltech groups: Division of Physics, Mathematics and Astronomy (PMA) , Physics Department
Publication Status: Published

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DELVE Milky Way Satellite Galaxy Census. I. Satellite Population and Survey Selection Function in DES, DELVE, and Pan-STARRS

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DELVE Milky Way Satellite Galaxy Census. I. Satellite Population and Survey Selection Function in DES, DELVE, and Pan-STARRS

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