Reconstructing the three-dimensional local dark matter velocity distribution

Reconstructing the three-dimensional local dark matter velocity distribution
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重建三维局部暗物质速度分布

DOI:
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发表时间:
2016
期刊:
影响因子:
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通讯作者:
C. O’Hare
C. O’Hare
中科院分区:
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文献类型:
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作者:
B. Kavanagh;C. O’Hare

文献摘要

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方向敏感的暗物质(DM)直接探测实验目前唯一的方法来观察整个三维速度分布的银河系晕本地到地球。在这项工作中,我们比较方法提取信息的本地DM速度分布从一组反冲方向和能量在一系列假设的定向和非定向实验。我们比较了一个独立于模型的经验参数化的速度分布的基础上的角度离散与依赖于模型的方法,假设知识的函数形式的分布。三个不同的晕模型,其中包括一系列可能的相空间结构的局部速度分布:一个光滑的麦克斯韦晕,潮汐流和泥石流的方法进行了测试。在每种情况下,我们使用模拟的方向数据,试图重建的形状和参数描述每个模型以及DM粒子的属性。我们发现,经验参数化是能够准确无偏重建DM质量和横截面,以及捕获功能的底层速度分布在某些方向上,而无需任何假设其真正的功能形式。我们还发现,通过提取定向平均速度参数与这种方法可以区分晕模型与不同类别的子结构。
Directionally sensitive dark matter (DM) direct detection experiments present the only way to observe the full three-dimensional velocity distribution of the Milky Way halo local to Earth. In this work we compare methods for extracting information about the local DM velocity distribution from a set of recoil directions and energies in a range of hypothetical directional and nondirectional experiments. We compare a model-independent empirical parametrization of the velocity distribution based on an angular discretization with a model-dependent approach which assumes knowledge of the functional form of the distribution. The methods are tested under three distinct halo models which cover a range of possible phase space structures for the local velocity distribution: a smooth Maxwellian halo, a tidal stream and a debris flow. In each case we use simulated directional data to attempt to reconstruct the shape and parameters describing each model as well as the DM particle properties. We find that the empirical parametrization is able to make accurate unbiased reconstructions of the DM mass and cross section as well as capture features in the underlying velocity distribution in certain directions without any assumptions about its true functional form. We also find that by extracting directionally averaged velocity parameters with this method one can discriminate between halo models with different classes of substructure.