SEI: Collaborative Research: Discovering Unexpected Planets and Other Astronomical Oddities

IIS-0713273Alcock，Charles哈佛大学合作研究：发现意想不到的行星和其他天文学奇特现象该项目寻求提供自动方法来分析天空测量，以通过异常和新奇检测方法发现太阳系外行星。超大型天文观测仪不久将定期监测天空的大部分区域，探测到大量有趣、多变的天文物体。这项提议的目标是开发必要的工具来利用这些新数据，以推进发现。拟议的工作将从广泛的角度探索对光曲线(现在有6600万条光曲线，十年内增长到1000亿条)海量数据集的科学分析和建模。这一领域的数据所带来的独特复杂性将推动对数据挖掘技术的研究，以实现这些分析。将开发一个模型及其与数据的关系的综合框架，容易地将两种有趣的对象分开：(1)揭示关于模型的特殊见解的稀有对象；(2)无法由模型描述的潜在的真正新颖的对象。将为这些目的开发用于新颖性检测的新的计算容易处理的时间序列算法。

IIS - 0713273Alcock, CharlesHarvard UniversityCollaborative Research: Discovering Unexpected Planets and Other Astronomical OdditiesThis project seeks to provide automated methods for analyzing sky surveys to detect extra-solar planets via anomaly and novelty detection methods. Extremely large astronomical synoptic surveys will soon monitor much of the sky regularly, detecting vast numbers of interesting, variable astronomical objects. The objective of this proposal is to develop the tools necessary to exploit these new data in order advance discovery. The proposed work will explore the scientific analysis and modeling of massive datasets of light-curves (66 million light-curves now available, growing to 100 billion in a decade) from a broad range of perspectives. The unique complications posed by the data in this domain will drive research for data mining techniques to allow these analyses. A comprehensive framework of models and their relationships with the data will be developed that readily separates two kinds of interesting objects: (1) Rare objects that reveal special insights about the models; and (2) Potential truly novel objects that cannot be described by the models. New computationally tractable time series algorithms for novelty detection will be developed for these purposes.