Milky Way Satellite Census. I. The Observational Selection Function for Milky Way Satellites in DES Y3 and Pan-STARRS DR1

Drlica-Wagner, A.; Bechtol, K.; Mau, S.; McNanna, M.; Nadler, Ethan O.; Pace, Andrew B.; Li, Ting S.; Pieres, A.; Rozo, Eduardo; Simon, J. D.; Walker, A. R.; Wechsler, Risa H.; Abbott, T. M. C.; Allam, S.; Annis, J.; Bertin, E.; Brooks, D.; Burke, D. L.; Rosell, A. Carnero; Kind, M. Carrasco; Carretero, J.; Costanzi, M.; Costa, L. N. da; Vicente, J. De; Desai, S.; Diehl, H. T.; Doel, P.; Eifler, T. F.; Everett, S.; Flaugher, B.; Frieman, Joshua A.; García-Bellido, J.; Gaztañaga, E.; Gruen, David; Gruendl, R. A.; Gschwend, J.; Gutiérrez, G.; Honscheid, K.; James, D. J.; Krause, E.; Kuêhn, K.; Kuropatkin, N.; Lahav, O.; Maia, M. A. G.; Marshall, J. L.; Melchior, P.; Menanteau, F.; Miquel, R.; Palmese, A.; Malagón, A. A. Plazas; Sánchez, E.; Scarpine, V.; Schubnell, M.; Serrano, S.; Sevilla-Noarbe, I.; Smith, M.; Suchyta, E.; Tarlè, G.

doi:10.3847/1538-4357/ab7eb9

Cited by 163 publications

(147 citation statements)

References 160 publications

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“…In this Letter, we use novel measurements and modeling of the MW satellite galaxy population to constrain each DM paradigm described above. Specifically, we combine a census of MW satellites [33] from the Dark Energy Survey (DES) [34] and Pan-STARRS1 (PS1) [35] with a rigorous forward-modeling framework [36] to fit the positiondependent MW satellite luminosity function in each of these DM paradigms. This procedure fully incorporates inhomogeneities in the observed MW satellite population and marginalizes over uncertainties in the mapping between MW satellite galaxies and DM halos, the efficiency of subhalo disruption due to the MW disk, and the properties of the MW system.…”

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confidence: 99%

“…Fitting procedure.-We fit predicted satellite populations to the observed satellite population from DES and PS1 using the observational selection functions derived in Ref. [33], assuming that satellite surface brightness is distributed according to a Poisson point process in each survey footprint [36,57]. We use the Markov chain Monte Carlo code EMCEE [58] to simultaneously fit for seven parameters governing the galaxy-halo connection, one parameter governing the impact of the MW disk on subhalo disruption, and one parameter governing the impact of the DM model in question, which we express as a subhalo mass scale.…”

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confidence: 99%

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Constraints on Dark Matter Properties from Observations of Milky Way Satellite Galaxies

Nadler¹,

Drlica-Wagner²,

Bechtol³

et al. 2021

Phys. Rev. Lett.

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243

214

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confidence: 99%

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confidence: 99%

Constraints on Dark Matter Properties from Observations of Milky Way Satellite Galaxies

Nadler¹,

Drlica-Wagner²,

Bechtol³

et al. 2021

Phys. Rev. Lett.

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243

214

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“…We also require that satellite candidates consist of at least 3 RRab candidates. We quantify the sensitivity of our search using a suite of 10 5 simulated satellite galaxies generated by Drlica-Wagner et al (2020). These satellites span a range of stellar mass, heliocentric distance, size, ellipticity, and position angle (see Table 1 of Drlica-Wagner et al 2020).…”

Section: Search For New Satellite Galaxiesmentioning

confidence: 99%

“…We quantify the sensitivity of our search using a suite of 10 5 simulated satellite galaxies generated by Drlica-Wagner et al (2020). These satellites span a range of stellar mass, heliocentric distance, size, ellipticity, and position angle (see Table 1 of Drlica-Wagner et al 2020). The simulated satellites are distributed uniformly over the DES footprint and uniformly in distance modulus.…”

Section: Search For New Satellite Galaxiesmentioning

confidence: 99%

“…Based on the successful detection of RRL associated with known ultra-faint satellites, we use our catalog to perform a search for previously undiscovered satellite galaxies in the DES footprint. No high-confidence satellite galaxy candidates are discovered, and we interpret the sensitivity of our search in the context of a suite of satellite galaxy simulations from Drlica-Wagner et al (2020).…”

Section: Introductionmentioning

confidence: 97%

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Identifying RR Lyrae Variable Stars in Six Years of the Dark Energy Survey

Stringer

Drlica-Wagner

Macri

et al. 2021

ApJ

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We present a search for RR Lyrae stars using the full six-year data set from the Dark Energy Survey covering ∼5000 deg2 of the southern sky. Using a multistage multivariate classification and light-curve template-fitting scheme, we identify RR Lyrae candidates with a median of 35 observations per candidate. We detect 6971 RR Lyrae candidates out to ∼335 kpc, and we estimate that our sample is >70% complete at ∼150 kpc. We find excellent agreement with other wide-area RR Lyrae catalogs and RR Lyrae studies targeting the Magellanic Clouds and other Milky Way satellite galaxies. We fit the smooth stellar halo density profile using a broken-power-law model with fixed halo flattening (q = 0.7), and we find strong evidence for a break at R 0 = 32.1 − 0.9 + 1.1 kpc with an inner slope of n 1 = − 2.54 − 0.09 + 0.09 and an outer slope of n 2 = − 5.42 − 0.14 + 0.13 . We use our catalog to perform a search for Milky Way satellite galaxies with large sizes and low luminosities. Using a set of simulated satellite galaxies, we find that our RR Lyrae-based search is more sensitive than those using resolved stellar populations in the regime of large (r h ≳ 500 pc), low-surface-brightness dwarf galaxies. A blind search for large, diffuse satellites yields three candidate substructures. The first can be confidently associated with the dwarf galaxy Eridanus II. The second has a distance and proper motion similar to the ultrafaint dwarf galaxy Tucana II but is separated by ∼5 deg. The third is close in projection to the globular cluster NGC 1851 but is ∼10 kpc more distant and appears to differ in proper motion.

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No room to hide: implications of cosmic-ray upscattering for GeV-scale dark matter

Alvey

Bringmann

Kolešová

2023

J. High Energ. Phys.

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The irreducible upscattering of cold dark matter by cosmic rays opens up the intriguing possibility of detecting even light dark matter in conventional direct detection experiments or underground neutrino detectors. The mechanism also significantly enhances sensitivity to models with very large nuclear scattering rates, where the atmosphere and rock overburden efficiently stop standard non-relativistic dark matter particles before they could reach the detector. In this article, we demonstrate that cosmic-ray upscattering essentially closes the window for strongly interacting dark matter in the (sub-)GeV mass range. Arriving at this conclusion crucially requires a detailed treatment of both nuclear form factors and inelastic dark matter-nucleus scattering, as well as including the full momentum-transfer dependence of scattering amplitudes. We illustrate the latter point by considering three generic situations where such a momentum-dependence is particularly relevant, namely for interactions dominated by the exchange of light vector or scalar mediators, respectively, and for dark matter particles of finite size. As a final concrete example, we apply our analysis to a putative hexaquark state, which has been suggested as a viable baryonic dark matter candidate. Once again, we find that the updated constraints derived in this work close a significant part of otherwise unconstrained parameter space.

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Milky Way Satellite Census. I. The Observational Selection Function for Milky Way Satellites in DES Y3 and Pan-STARRS DR1

Cited by 163 publications

References 160 publications

Constraints on Dark Matter Properties from Observations of Milky Way Satellite Galaxies

Constraints on Dark Matter Properties from Observations of Milky Way Satellite Galaxies

Identifying RR Lyrae Variable Stars in Six Years of the Dark Energy Survey

No room to hide: implications of cosmic-ray upscattering for GeV-scale dark matter

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