INSPIRE Track 1: Arizona-NOAO Temporal Analysis and Response to Events System (ANTARES)

这个INSPIRE奖部分由天文科学司和多学科活动办公室的特别项目计划资助，这两个部门都在数学和物理科学局，以及计算机和信息科学与工程局信息和智能系统处的信息技术研究和信息集成与信息学计划。该项目将构建一个用于过滤和注释由天文时域勘测生成的警报的软件基础设施，其中警报是与参考图像相比时天文源的变化。 当前和未来的巡天能够产生大量的此类警报：特别是，计划中的大型综合巡天望远镜项目可以在十年内每晚产生100万或更多的警报。 在这场真正的洪水中，将有少数罕见和不寻常的短寿命源，必须在真实的时间内识别出来，否则将失去彻底研究的机会。这项研究将满足这一需求：该系统将包括一个核心流程，该流程可以快速地用已知的细节注释警报，在第一次通过时创建一个有用的数据库，随后是一种方法，以获得广泛的特性特征，这些特性特征可用于过滤掉并转移那些不需要快速跟踪的事件。 高级的、计算量更大的处理可以应用于通过过滤器的那些，包括允许用户根据其特定兴趣进行选择的多个路径。 这个原型的最终产品是那些最不寻常的警报。 该系统的设计非常灵活，因此不会丢失警报，并且外部用户可以在任何时候对数据流进行处理。 使用亚利桑那州机器实验室允许模型的构建和测试，并创建新颖的，也许更有效的，过滤过程。 对已知但罕见的天体的研究将改变从恒星演化到活动星系核的生长再到宇宙基本结构的各个领域，而对以前未知天体的发现和表征则可能创造全新的领域。 虽然原型将专注于最稀有的对象，但最终内置的灵活性和社区生成的过滤过程将使任何用户都能够找到特定感兴趣的项目。 此外，一个可以接收警报、汇总辅助信息并过滤以识别特定病例的系统将在许多领域中普遍使用，从流行病学到网络保护，再到国土安全等，只要快速分析与现有信息适当关联的新事件至关重要。

This INSPIRE award is partially funded by the Special Projects program of the Division of Astronomical Sciences and the Office of Multidisciplinary Activities, both in the Directorate for Mathematical and Physical Sciences, and by the Information Technology Research and Information Integration and Informatics programs in the Division of Information and Intelligent Systems in the Directorate for Computer and Information Science and Engineering.This project will construct a software infrastructure for filtering and annotating alerts generated by astronomical time-domain surveys, where an alert is a change in an astronomical source when compared with a reference image. Current and future surveys are capable of producing enormous numbers of such alerts: in particular, the planned Large Synoptic Survey Telescope project could produce a million or more every single night for a decade. Within this veritable flood will be a small number of rare and unusual sources with short lifetimes that must be recognized in real time, or else the opportunity for thorough study will be lost.This research will meet that need: the system will include a core flow that quickly annotates alerts with already known details, creating a useful database in its very first pass, followed by a method to derive broad characteristic features that can be used to filter out and divert those events not in need of rapid follow-up. Advanced, more computationally intensive processing can be applied to those that pass the filters, including multiple paths that allow users to select for their particular interests. The final product for this prototype is those alerts that are the most unusual. The system is designed to be flexible, so no alerts are lost and the stream can be tapped by external users at any point for their own processing. Use of the Arizona Machine Experimentation Lab allows for model construction and testing, and for creation of novel, perhaps more efficient, filtering processes. Throughout, decisions are completely driven by astronomical expertise.The study of known but rare objects will transform fields ranging from stellar evolution to growth of active galactic nuclei to the fundamental structure of the Universe, while the discovery and characterization of previously unknown objects could create entirely new fields. Although the prototype will focus on the rarest of objects, ultimately the built-in flexibility and community-generated filtering processes will enable finding items of specific interest to any user. In addition, a system that can take alerts, aggregate ancillary information, and filter to identify specific cases, will be of general use in many fields, from epidemiology to network protection to homeland security and beyond, wherever rapid analysis of new events properly associated with existing information is critical.