NSF CDSE: Enabling Precise Constraints on Dark Energy

NSF CDSE：实现对暗能量的精确约束

• 批准号: 1313415
• 负责人: Robert Brunner
• 金额: $ 54.47万
• 依托单位: University of Illinois at Urbana-Champaign
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-01 至 2018-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1313415&HistoricalAwards=false
• 关键词: NSF; CDSE; Enabling; Precise; Constraints

This goal of this proposal is to develop advanced techniques to calculate accurate and computationally efficient photometric redshift distance estimators, and to mitigate photometric uncertainties and systematics on clustering measures for galaxies found in large numbers in current and upcoming surveys. The computer codes will incorporate machine learning techniques with a combination of supervised and unsupervised learning algorithms. The methods developed will be applicable to the massive surveys to be undertaken by the future Large Synoptic Survey Telescope, which will, among other things, place precise constraints on Dark Energy. Broader impacts of the work include training of a postdoc, a graduate student, and undergraduate students, and development of a course in Data Science to be available on line. All computational tools developed will be made available to the general astronomical community.

本提案的目标是开发先进的技术，以计算准确和计算效率高的光度红移距离估计，并减轻光度不确定性和系统性的集群措施，发现大量的星系在当前和即将到来的调查。 计算机代码将结合机器学习技术和监督和无监督学习算法。所开发的方法将适用于未来大型综合巡天望远镜进行的大规模巡天，除其他外，该望远镜将对暗能量进行精确的限制。 这项工作的更广泛影响包括培训博士后，研究生和本科生，以及开发在线数据科学课程。 开发的所有计算工具将提供给一般天文学界。