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The expected gamma-ray flux coming from dark matter annihilation in dwarf spheroidal (dSph) galaxies depends on the so-called J-factor, the integral of the squared dark matter density along the line of sight. We examine the degree to which estimates of J are sensitive to contamination (by foreground Milky Way stars and stellar streams) of the stellar-kinematic samples that are used to infer dark matter densities in 'ultrafaint' dSphs. Applying standard kinematic analyses to hundreds of mock data sets that include varying levels of contamination, we find that misclassified contaminants can cause J-factors to be overestimated by orders of magnitude. Stellar-kinematic data sets for which we obtain such biased estimates tend (1) to include relatively large fractions of stars with ambiguous membership status, and (2) to give estimates for J that are sensitive to specific choices about how to weight and/or to exclude stars with ambiguous status. Comparing publicly available stellar-kinematic samples for the nearby dSphs Reticulum II and Segue I, we find that only the latter displays both of these characteristics. Estimates of Segue I's J-factor should therefore be regarded with a larger degree of caution when planning and interpreting gamma-ray observations. Moreover, robust interpretations regarding dark matter annihilation in dSph galaxies in general will require explicit examination of how interlopers might affect the inferred dark matter density profiles. [ABSTRACT FROM AUTHOR]

Dwarf spheroidal (dSph) galaxies are prime targets for present and future Y -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 optimized 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 minimize 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 parametrization we use results in changes compared to previous calculations. This translates into our ranking of potentiallybrightest and most robust targets - namely Ursa Minor, Draco, Sculptor - and of the more promising, but uncertain targets - namely 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. [ABSTRACT FROM AUTHOR]

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 optimized 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 minimize 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 parametrization we use results in changes compared to previous calculations. This translates into our ranking of potentially-brightest and most robust targets - namely Ursa Minor, Draco, Sculptor - and of the more promising, but uncertain targets - namely 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. [ABSTRACT FROM AUTHOR]

Dwarf spheroidal (dSph) galaxies are among the most promising targets for the indirect detection of dark matter (DM) from annihilation and/or decay products. Empirical estimates of their DM content - and hence the magnitudes of expected signals - rely on inferences from stellar-kinematic data. However, various kinematic analyses can give different results and it is not obvious which are most reliable. Using extensive sets of mock data of various sizes (mimicking 'ultrafaint' and 'classical' dSphs) and a Markov Chain Monte Carlo engine, here we investigate biases, uncertainties and limitations of analyses based on parametric solutions to the spherical Jeans equation. For a variety of functional forms for the tracer and DM density profiles, as well as the orbital anisotropy profile, we examine reliability of estimates for the astrophysical J- and D-factors for annihilation and decay, respectively. For large (N ≳ 1000) stellar-kinematic samples, typical of 'classical' dSphs, errors tend to be dominated by systematics, which can be reduced through the use of sufficiently general and flexible functional forms. For small (N ≲ 100) samples typical of 'ultrafaints', statistical uncertainties tend to dominate systematic errors and flexible models are less necessary. We define an optimal strategy that would mitigate sensitivity to priors and other aspects of analyses based on the spherical Jeans equation. We also find that the assumption of spherical symmetry can bias estimates of J (with the 95?per?cent credibility intervals not encompassing the true J-factor) when the object is mildly triaxial (axis ratios b/a = 0.8, c/a = 0.6). A concluding table summarizes the typical error budget and biases for the different sample sizes considered. [ABSTRACT FROM AUTHOR]