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

SEI：合作研究：发现意想不到的行星和其他天文奇异现象

• 批准号: 0713259
• 负责人: Carla Brodley
• 金额: $ 20.59万
• 依托单位: Tufts University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-09-15 至 2011-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0713259&HistoricalAwards=false
• 关键词: SEI; Collaborative; Research; Discovering; Unexpected

This 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.

该项目旨在提供自动化方法，用于分析通过异常和新颖性检测方法来检测太阳外行星的自动化方法。非常大的天文概要调查将很快定期监视天空的大部分，从而检测出大量有趣的可变天文对象。该提案的目的是开发利用这些新数据的必要工具，以提前发现。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6600万光弯曲曲线，在十年内增长到1000亿）。该域中数据构成的独特并发症将推动数据挖掘技术的研究以允许这些分析。将开发一个综合模型及其与数据的关系，很容易将两种有趣的对象分开：（1）稀有对象揭示了有关模型的特殊见解； （2）模型无法描述的潜在真正新颖对象。出于这些目的，将开发用于新颖性检测的新的计算可拖动时间序列算法。