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Dark matter annihilation and decay in dwarf spheroidal galaxies: The classical and ultrafaint dSphs

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Dwarf spheroidal (dSph) galaxies are prime targets for present and future γ-ray telescopes hunting for indirect signals of particle dark matter. The interpretation of the data requires careful assessment of their dark matter content in order to derive robust constraints on candidate relic particles. Here, we use an optimised spherical Jeans analysis to reconstruct the 'astrophysical factor' for both annihilating and decaying dark matter in 21 known dSphs. Improvements with respect to previous works are: (i) the use of more flexible luminosity and anisotropy profiles to minimise biases, (ii) the use of weak priors tailored on extensive sets of contamination-free mock data to improve the confidence intervals, (iii) systematic cross-checks of binned and unbinned analyses on mock and real data, and (iv) the use of mock data including stellar contamination to test the impact on reconstructed signals. Our analysis provides updated values for the dark matter content of 8 'classical' and 13 'ultrafaint' dSphs, with the quoted uncertainties directly linked to the sample size; the more flexible parametrisation we use results in changes compared to previous calculations. This translates into our ranking of potentially-brightest and most robust targets—viz., Ursa Minor, Draco, Sculptor—, and of the more promising, but uncertain targets—viz., Ursa Major 2, Coma—for annihilating dark matter. Our analysis of Segue 1 is extremely sensitive to whether we include or exclude a few marginal member stars, making this target one of the most uncertain. Our analysis illustrates challenges that will need to be addressed when inferring the dark matter content of new 'ultrafaint' satellites that are beginning to be discovered in southern sky surveys.
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... The standard methodology to compute the J-factor for the dSphs is to compare solutions from the spherical Jeans equation to the observed velocity dispersion to infer the underlying properties of the dSph dark matter halo (e.g., Bonnivard et al. 2015;Geringer-Sameth et al. 2015;Pace & Strigari 2019). We follow Pace & Strigari (2019) to compute the J-factor, which assumes the stellar distribution to follow a Plummer model (Plummer 1911), a Navarro-Frenk-White model for the dark matter halo (Navarro et al. 1996), and constant stellar anisotropy with radius. ...
... We note that the two apparent outliers at v hel ≈ −15 km s −1 with large error bars are the BHBs discussed in Section 4.1. . We note that some large J-factors in the literature should be treated with caution; for example, Wil 1 may be tidally disrupting (Willman et al. 2011) and has a small pericenter (∼12 kpc Pace et al. 2022), the velocity dispersion of Tuc II has decreased by a factor of 2 with larger samples (Chiti et al. 2023), different stellar density profiles of Hor I lead to a factor of 2 uncertainty in the J-factor (Pace & Strigari 2019), and the membership choices of the spectroscopic sample impact the Seg 1 J-factor (Bonnivard et al. 2015). Compared to the general dSph population, Eri IV has a relatively large J-factor whereas Cen I is unremarkable as it is similar to dSphs at similar distances. ...
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... To optimize the size of the ROI for balancing the preference between a larger area containing more signal and a smaller area with less background (and nearby sources) contamination, we utilize S/ √ B as a metric, where S and B are the expected signal and expected background in the ROI, respectively. Considering the expected signal also depends on the details of NFW profile [39][40][41], we use the publicly available MCMC chains provided by Ref. [41] to determine the optimal ROI for our instrument and compute the corresponding J-(D-) factor distribution in our ROI. The details are discussed in Sec. ...
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