Accounting for Distance Errors in Cosmology

星系和类星体的光度函数提供了关于它们形成的宝贵信息。如果对象具有准确的已知距离，则从大小受限的样本估计光度函数是简单的，但当距离仅是近似值或仅对于样本的一小部分众所周知时，则困难得多。例如，当光度学红移可用，但光谱红移不可用时，就会发生这种情况。这项研究将开发算法来处理这种复杂性，并处理这些不确定性对内在属性相关性的影响。开发的算法将被用来解释来自星系和类星体调查的数据。这些方法将影响广泛的天文学研究，包括附近具有显著特殊速度的星系，以及在无法获得准确视差距离时的恒星光度函数。由于这项工作在三年的时间线上融合了理论和数据分析，它也非常适合博士论文项目，并将尽一切努力从代表不足的群体中招募一名有能力的研究生。

AST-0507501ShethThe luminosity functions of galaxies and quasars provide invaluable information about their formation. Estimating the luminosity function from magnitude-limited samples is straightforward if the objects have accurately known distances, but much more difficult when distances are only approximate, or only well known for a small subset of the sample. This occurs, for example, when photometric redshifts are available, but spectroscopic redshifts are not. This research will develop algorithms to handle this complication, and to cope with the effects of these uncertainties on correlations of intrinsic properties. The developed algorithms will be used to interpret data from galaxy and quasar surveys that are just becoming available.These methods will impact a broad range of astronomical studies, including nearby galaxies with marked peculiar velocities, and stellar luminosity functions when accurate parallax distances are not available. Since the work blends theory and data analysis over a three year timeline, it is also well suited for a doctoral thesis project, and every effort will be made to enlist a capable graduate student from an under-represented group.