标题： 钱德拉-ACIS观测分析的创新 显示英文标题

标题： Innovations in the Analysis of Chandra-ACIS Observations

摘要： 作为美国宇航局钱德拉X射线天文台高级CCD成像光谱仪（ACIS）仪器团队的成员以及钱德拉普通观测者，我们开发了一系列我们认为对钱德拉社区有用的资料分析方法，并构建了大量公开可用的软件包（ACIS提取包），以解决重要的ACIS数据和科学分析任务。 本文旨在描述这些资料分析方法有两个目的：记录我们在自己的科学研究项目中完成的数据分析工作，帮助其他ACIS观测者判断这些方法是否可能对他们自己的项目有用（无论他们选择使用什么工具和程序来实施这些方法）。 我们提供的ACIS数据分析建议涵盖了典型ACIS项目中的大部分工作流程，包括数据准备、通过小波分解和图像重建检测点源、屏蔽点源、识别弥散结构、点源和弥散源的事件提取、合并多个观测的提取结果、非参数宽带测光、低计数光谱分析，以及这些任务的自动化。 这里介绍的许多创新方法来源于钱德拉项目的许多常见且常常交织在一起的复杂情况：大量的点源（数百到数千个）、微弱的点源、天体领域的多观测偏移、点源拥挤，以及与科学相关的弥散辐射。 显示英文摘要

摘要： As members of the instrument team for the Advanced CCD Imaging Spectrometer (ACIS) on NASA's Chandra X-ray Observatory and as Chandra General Observers, we have developed a wide variety of data analysis methods that we believe are useful to the Chandra community, and have constructed a significant body of publicly-available software (the ACIS Extract package) addressing important ACIS data and science analysis tasks. This paper seeks to describe these data analysis methods for two purposes: to document the data analysis work performed in our own science projects, and to help other ACIS observers judge whether these methods may be useful in their own projects (regardless of what tools and procedures they choose to implement those methods). The ACIS data analysis recommendations we offer here address much of the workflow in a typical ACIS project, including data preparation, point source detection via both wavelet decomposition and image reconstruction, masking point sources, identification of diffuse structures, event extraction for both point and diffuse sources, merging extractions from multiple observations, nonparametric broad-band photometry, analysis of low-count spectra, and automation of these tasks. Many of the innovations presented here arise from several, often interwoven, complications that are found in many Chandra projects: large numbers of point sources (hundreds to several thousand), faint point sources, misaligned multiple observations of an astronomical field, point source crowding, and scientifically relevant diffuse emission.