矮球状星系中暗物质间接探测的球形金斯分析.物理参数和三轴度的影响
Spherical Jeans analysis for dark matter indirect detection in dwarf spheroidal galaxies - Impact of physical parameters and triaxiality
摘要：
矮椭球星系是间接探测湮灭和/或衰变产物中暗物质最有希望的目标之一。它们的DM内容的经验估计-因此预期信号的大小-依赖于从恒星运动学数据的推断。然而，不同的运动学分析可以给出不同的结果，这是不明显的，这是最可靠的。使用大量的模拟数据集的各种大小（模仿“超微弱”和“经典”dSphs）和MCMC引擎，在这里，我们调查的偏见，不确定性和局限性的分析的基础上参数的解决方案，以球面牛仔方程。对于各种功能形式的示踪剂和DM密度分布，以及轨道各向异性配置文件，我们检查的可靠性估计的天体物理J-和D-因子的湮灭和衰变，分别。对于典型的“经典”dSphs的大（N > 1000）恒星运动学样本，误差往往由系统学控制，这可以通过使用足够通用和灵活的函数形式来减少。对于小样本（N < 100）典型的“超模糊”，统计不确定性往往占主导地位的系统误差和灵活的模型是不太必要的。我们定义了一个最佳的策略，将减轻敏感性的先验知识和其他方面的分析的基础上，球面牛仔方程。我们还发现，球对称的假设可以偏差估计J（95%的可信区间不包括真正的J因子）时，对象是轻度三轴（轴比b/a = 0.8，c/a = 0.6）。总结表总结了所考虑的不同样本量的典型误差预算和偏倚。
英文摘要：
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 'ultra-faint' and 'classical' dSphs) and an MCMC 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% 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 summarises the typical error budget and biases for the different sample sizes considered.
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