A Geometric Framework for the Exploration and Analysis of Astrophysical Data

当今天文学面临的主要挑战之一是组织和分析计算机和数据收集技术的最新进展所提供的大量数据。该项目汇集了计算几何、机器学习和天体物理学方面的研究人员的努力，以开发和应用计算技术来帮助分析和合成天体物理数据。该项目的目标是为天体物理学研究界提供计算技术，该技术体现在一个名为AstroExplorer的软件系统中，用于分析非常大、复杂的多参数数据集。具体地说，该项目将为执行一般类型的数据提取、跨数据库的数据合成和集群分析提供新的范例。所有方法都基于统一的框架，即查看数据点和对其进行几何操作的统一框架。这项工作通过提供处理几何数据的方法扩展了当前的数据库技术。这种方法应大大提高天文学家在数据收集和存储革命产生的海量数据中的搜索效率，因为它为他们提供了一种计算工具，用于提取与特定几何图案相匹配的数据，或者可以通过基于自然和直观的几何概念的方法将数据聚集在一起。

One of the main challenges facing Astronomy today involves the organization and analysis of the vast volumes of data that has been provided by recent advances in computer and data-collecting technology. This project pools the efforts of researchers in computational geometry, machine learning, and astrophysics in order to develop and apply computational techniques to aid in the analysis and synthesis of astrophysical data. The goal of this project is to provide the astrophysical research community with computational techniques, embodied in a software system called AstroExplorer, for analyzing very large, complex, multi-parameter data sets. Specifically, this project will provide new paradigms for performing general kinds of data extraction, data synthesis across databases, and cluster analysis. All of the methods are based on the unifying framework of viewing data points and the operations that act upon them geometrically. This work extends the current database technology by providing methods for dealing with geometrical data. This approach should significantly improve the productivity of astronomers in their search through the oceans of data that have been produced by the revolution in data collection and storage, for it gives them a computational tool for extracting data that match specified geometric patterns or can be clustered by methods based on natural and intuitive geometric concepts.