Collaborative Research: Highly Structured Models and Statistical Computation in High-Energy Astrophysics

合作研究：高能天体物理中的高度结构化模型和统计计算

• 批准号: 0406085
• 负责人: David van Dyk
• 金额: $ 34.38万
• 依托单位: University of California-Irvine
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-08-15 至 2008-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0406085&HistoricalAwards=false
• 关键词: Collaborative; Research; Highly; Structured; Models

Pricipal Investigators: David Van Dyk and Xiao-Li MengInstitutions: UC Riverside and Harvard UniversityCollaborative Research: Highly Structured Models and Statistical Computation in High-Energy AstrophysicsAbstractThe California-Harvard Astrostatistics Collaboration aims to designand implement fully model-based methods of statistical inference tosolve outstanding data analytic problems in high-energyastrophysics. The Collaboration's methods explicitly model thecomplexities of both astronomical sources and the data generationmechanisms inherent in new high-tech instruments and fully utilize theresulting highly structured models in learning about the underlyingastronomical and physical processes. Using these models requiressophisticated scientific computation, advanced methods for statisticalinference, and careful model checking procedures. The PIs of theCollaboration (van Dyk and Meng) both have substantial researchexperience in developing the methods that the Collaboration isextending, employing, and publicizing: inferential and efficientcomputational methods under highly-structured models that involvemultiple levels of latent variables and incomplete data. Such modelsare ideally suited to account for the many physical and instrumentalfilters that compose the data generation mechanism in high-energyastrophysics. The five consultants on the project (Chiang, Connors,Kashyap, Karovska, and Siemiginowska) all have expertise on theinstrumentation and science of high-energy astrophysics, and, all havecollaborated with statisticians in efforts to develop appropriatemethods to address scientific questions. There are two primary impactsof this project: the impact of the development of more reliablestatistical methods on scientific findings in astronomy and the impactof the new statistical inference and computation methods in a widerange of scientific fields. As the Collaboration develops methods anddistributes free software for specific inferential tasks, it alsoeducates the astronomical community as to the benefit of careful useof sophisticated statistical methods. (The Collaboration organizes oneor two special sessions at meetings of the American AstronomicalSociety each year.) It is expected that a fundamental impact of theproposed research will be a more general acceptance and more prevalentuse of appropriate methods among astronomers. Second, theCollaboration is an example of a new mode of statisticalinference. Rather than using off-the-shelf models and methods, it isbecoming ever more feasible to develop application specific modelsthat are designed to account for the particular complexities of aproblem at hand. The Collaboration develops inferential andcomputational methods for handling such multi-level models. Asapplication specific multi-level models become more prevalent, thesemethods will have application throughout the natural, social, andengineering sciences.In recent years, there has been an explosion of new data inobservational high-energy astrophysics. Recently launched orsoon-to-be launched space-based telescopes that are designed to detectand map ultra-violet, X-ray, and gamma-ray electromagnetic emissionare opening a whole new window to study the cosmos. Because theproduction of high-energy electromagnetic emission requirestemperatures of millions of degrees and is an indication of therelease of vast quantities of stored energy, these instruments give acompletely new perspective on the hot and turbulent regions of theuniverse. The new instrumentation allows for very high resolutionimaging, spectral analysis, and time series analysis. The ChandraX-ray Observatory, for example, produces images at least thirty timessharper than any previous X-ray telescope. The complexity of theinstruments, the complexity of the astronomical sources, and thecomplexity of the scientific questions leads to a subtle inferenceproblem that requires sophisticated statistical tools. For example,data are subject to non-uniform censoring, errors in measurement, andbackground contamination. Astronomical sources exhibit complex andirregular spatial structure. Scientists wish to draw conclusions as tothe physical environment and structure of the source, the processesand laws which govern the birth and death of planets, stars, andgalaxies, and ultimately the structure and evolution of theuniverse. Nonetheless little effort has been made to bring thestrength of modern statistical methods to bare on these problems. TheCalifornia-Harvard Astrostatistics Collaboration develops statisticalmethods, computational techniques, and freely available software toaddress outstanding inferential problems in high-energy astrophysics.The methods developed are an example of a new mode of statisticalinference: Rather than using off-the-shelf methods, it is becomingever more feasible to develop methods that are application specificand are designed to account for the particular complexities of aproblem at hand. The inferential and computational methods designed bythe Collaboration for handling such multi-level models haveapplication throughout the natural, social, and engineering sciences.

主要研究人员：David Van Dyk和孟晓丽：加州大学河滨分校和哈佛大学合作研究：高能天体物理中的高度结构模型和统计计算摘要加州-哈佛天体统计合作旨在设计和实现完全基于模型的统计推理方法，以解决高能天体物理中突出的数据分析问题。该合作的方法明确地模拟了新的高科技仪器所固有的复杂的天文来源和数据生成机制，并充分利用所产生的高度结构化的模型来了解潜在的天文和物理过程。使用这些模型需要复杂的科学计算、先进的统计推理方法和仔细的模型检验程序。The Collaboration的PI(van Dyk和Meng)在开发合作正在扩展、使用和宣传的方法方面都拥有丰富的研究经验：在涉及多个级别的潜在变量和不完整数据的高度结构化模型下的推理和高效计算方法。这类模型非常适合于解释高能天体物理学中构成数据生成机制的许多物理和仪器过滤器。该项目的五名顾问(Chiang、Connors、Kashyap、Karovska和Siemiginowska)都拥有高能天体物理仪器和科学方面的专业知识，并都与统计学家合作，努力制定适当的方法来解决科学问题。该项目有两个主要影响：更可靠的统计方法的发展对天文学科学发现的影响，以及新的统计推断和计算方法在更广泛的科学领域的影响。随着合作开发方法并为特定的推断任务分发免费软件，它还教育天文学社区谨慎使用复杂的统计方法的好处。(该合作组织每年在美国天文学会的会议上组织一到两次特别会议。)预计拟议研究的根本影响将是天文学家更普遍地接受和更普遍地使用适当的方法。其次，合作是一种新的统计推理模式的例子。与使用现成的模型和方法相比，开发特定于应用程序的模型来解决手头问题的特定复杂性正变得越来越可行。这项合作开发了处理这种多层次模型的推论和计算方法。随着特定应用的多层次模型变得更加普遍，这些方法将在自然科学、社会科学和工程科学中得到应用。近年来，观测高能天体物理中的新数据呈爆炸式增长。最近发射或即将发射的空间望远镜，旨在探测和绘制紫外线、X射线和伽马射线电磁辐射的地图，为研究宇宙打开了一扇全新的窗口。由于高能电磁辐射的产生需要数百万度的温度，而且是释放大量储存能量的标志，这些仪器为观察宇宙中炎热和动荡的区域提供了全新的视角。这种新仪器可用于非常高分辨率的成像、光谱分析和时间序列分析。例如，钱德拉X射线天文台产生的图像比以往任何一台X射线望远镜的清晰度至少高出30倍。仪器的复杂性、天文来源的复杂性和科学问题的复杂性导致了一个微妙的推断问题，需要复杂的统计工具。例如，数据受到不统一审查、测量误差和背景污染的影响。天文源具复杂而规则的空间结构。科学家们希望得出关于源的物理环境和结构、支配行星、恒星和星系的诞生和死亡的过程和规律，以及最终宇宙的结构和演化的结论。尽管如此，几乎没有做出什么努力来展示现代统计方法在这些问题上的力量。加州-哈佛天体统计学合作开发了统计方法、计算技术和免费软件，以解决高能天体物理中突出的推断问题。开发的方法是统计推理新模式的一个例子：与使用现成的方法相比，开发特定于应用程序的方法并针对手头问题的特殊复杂性进行设计变得更加可行。合作伙伴为处理这种多层次模型而设计的推理和计算方法在整个自然、社会和工程科学中都有应用。