AI 中文总结
研究银河系类星系中暗物质的通用分布，通过简单坐标变换揭示其分布函数，利用运动学特征图和机器学习分类器验证，还能从贫金属星推断坐标变换参数，构建归一化流模型，后续将应用于相关巡天数据。
AI 中文摘要
银河系内暗物质的相空间密度是编码暗物质领域性质信息的关键量，也是正确解释暗物质直接探测实验结果所必需的，但目前观测约束较少。本文表明，简单的坐标变换揭示了银河系质量星系的三个独立宇宙学模拟套件之间近乎通用的暗物质相空间分布函数。通过运动学特征图以及对全多变量相空间中所有相关性敏感的基于机器学习的分类器提供了证据。仅在星系半径和/或速度的极端情况下以及在一个有突出吸积暗盘的模拟中发现了与通用性的偏差。还表明坐标变换参数可从贫金属星（$\log_{10}[{\rm Fe}/{\rm H}]< -2$）推断出来，这些星也包含暗盘的特征，从而可从观测推断其存在。最后，使用归一化流构建了这个通用相空间分布的模型，并在跨模拟的标准化相空间上进行训练。后续工作将应用该方法处理盖亚和斯隆数字巡天的数据。
英文摘要
The phase-space density of dark matter within the Milky Way is a key quantity that encodes information about the nature of the dark sector. The local phase-space density is also required to properly interpret the results of dark matter direct detection experiments. However, there are at present few observational constraints. In this paper, we show that a simple coordinate transformation reveals a near-universal DM phase-space distribution function among three independent suites of cosmological simulations of Milky Way-mass galaxies. We provide evidence for this with plots of kinematic features as well as machine learning-based classifiers that are sensitive to all of the correlations in the full multivariate phase space. Deviations from universality are found only at extremes of galactic radius and/or velocity, and in one simulation that has a prominent accreted dark disc. We further show that the parameters for the coordinate transformation can be inferred from metal poor stars ($\log_{10}[{\rm Fe}/{\rm H}]< -2$). These stars also contain signatures of the dark disk, allowing the existence of such a structure to be inferred from observation. Finally, we construct a model of this universal phase-space distribution using a normalizing flow, trained on the standardized phase-space across simulations. We will apply our method to survey data from Gaia and SDSS in a forthcoming work.
Comments36 pages, 12 figures
