Global Statistical Models of the Galaxy

AST-9619516 银河系的全球统计模型。 哈佛大学的Kochanek和Di Stefano博士将整合各种各样的观测数据集，以得出银河系结构的模型。 他们将在定义明确的统计分析中使用距离估计值，动态数据和微透镜数据的组合。 确定银河系模型的要素包括到银河系中心的距离尺度、旋转曲线、盘的质量和形状、棒的性质、晕结构和银河系卫星的轨道特征。 与对银河系上孤立的数据片段进行建模相比，全局模型的优势在于，所有数据必须在一个共同的质量分布上达成一致的约束是一个非常强大的约束。 这样的模型和现实的估计其不确定性的关键估计银河系的暗物质分布，限制或确定非轴对称的数量，解释引力微透镜调查的结果，并了解银河系的组件的分布。 ===============================

AST-9619516 Global Statistical Models of the Galaxy. Drs. Kochanek and Di Stefano, at Harvard University, will integrate a wide variety of observational data sets in order to derive a model for the structure of the Galaxy. They will use a combination of distance estimators, dynamical data, and microlensing data in a well-defined statistical analysis. The elements of the Galactic model to be determined include the distance scale to the Galactic Center, the rotation curve, the disk mass and shape, the properties of the bar, the halo structure, and orbital characteristics of Galactic satellites. The advantage of global models, as compared to modeling isolated pieces of data on the Galaxy, is that the constraint that all data must agree on a common mass distribution is an extraordinarily powerful constraint. Such models and realistic estimates of their uncertainties are the key to estimating the dark matter distribution of the Galaxy, limiting or determining the amount of non-axisymmetry, interpreting the results of gravitational microlensing surveys, and understanding the distribution of Galactic components. ===============================