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

阿尔科克，查尔斯，哈佛大学合作研究：发现意想不到的行星和其他天文奇怪现象该项目旨在通过异常和新奇的探测方法，为分析天空调查提供自动化方法，以探测太阳系外行星。非常大的天文天气巡天很快就会定期监测大部分天空，探测到大量有趣的、多变的天文物体。本提案的目标是开发必要的工具来利用这些新数据，以便提前发现。拟议的工作将从广泛的角度探索大量光曲线数据集的科学分析和建模（现在有6600万条光曲线，十年后将增长到1000亿条）。该领域中数据所带来的独特复杂性将推动数据挖掘技术的研究，以允许这些分析。模型及其与数据关系的综合框架将被开发出来，可以很容易地分离出两种有趣的对象：(1)揭示关于模型的特殊见解的稀有对象；(2)模型无法描述的潜在的真正新颖的对象。新的计算易于处理的时间序列算法的新颖性检测将发展为这些目的。

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.