MSPA-AST: Advancing Statistical Methodology in Massive Astronomical Surveys

AST-0707833 Babu这是一个跨学科，多研究者，多方面的天文统计研究项目，连接天文学和统计学领域。 当前和未来的天文学研究涉及大量的成像，光度和光谱调查，产生TB到PB的数据库。 虽然科学前景是巨大的，但实现这些目标关键取决于从如此大的数据集中提取有用知识的能力。 统计问题是多种多样的，天文学家通常面临着先进方法的知识不足，由于有限的培训和不够集中的方法研究，该项目的最初计划包括一个大范围的活动，包括可能性和rescue方法，光度红移的多元方法，多元数据集的局部分类;用高效的计算算法分析大型数据集;以及对低分辨率光谱进行分类。 所资助的项目将涵盖这些专题中的一小部分，这将随着工作的进展而确定，教育和宣传工作仍然是工作的一大部分，包括组织继续举办年度统计推断强化暑期学校，但没有得到本奖项的资助。 然而，所有这些工作将对天文测量科学的统计质量和许多年轻研究人员的培训产生重大影响。

AST-0707833BabuThis is a cross-disciplinary, multi-investigator, multi-faceted suite of astro-statistical research projects bridging the fields of astronomy and statistics. Current and future astronomical research involves vast imaging, photometric and spectroscopic surveys that produce terabyte to petabyte databases. While the scientific promise is tremendous, achieving the goals depends critically on the ability to extract useful knowledge from such large datasets. The statistical problems are diverse, and astronomers typically confront them with inadequate knowledge of advanced methods, due both to limited training and to insufficiently focused methodological research.The original plan for this project included a large range of activities, covering likelihood and resampling methods, multivariate methods for photometric redshifts, the local classification of multivariate datasets; analysis of mega-datasets with efficient computational algorithms; and classification of low-resolution spectra. The project as supported will cover a rather smaller subset of these topics, to be determined as the work progresses.The education and dissemination work remains a large fraction of the effort, including organizing the continuation of an annual intensive Summer School in statistical inference, not supported by this award. All of this work will, however, have a substantial impact on both the statistical quality of astronomical survey science and on the training of many young researchers.