Collaborative Research: Optimal Statistics for Redshifted 21 cm Observations of the Reionization Epoch

宇宙学的一个重要的新前沿是再电离时代（Epoch of Reionization, EoR），它标志着宇宙中第一批发光物体形成的时间，以及宇宙结构形成的最后阶段。大多数研究人员试图通过探测星系间介质（IGM）的中性氢气，通过它在21厘米红移谱线上的特征来观察EoR。虽然目前正在进行各种项目来检测提高采收率信号，但热噪声将主导信号，并且需要对观测数据进行仔细的统计分析，以推断提高采收率信号的统计性质。不幸的是，采用的统计技术之一将是表征提高采收率信号的功率谱，即使该信号预计是非高斯的。这个项目的目的是系统地探索远远超出功率谱技术的统计。研究人员将为各种定义良好的理论模型计算再电离的辐射传输模拟。预期的热噪声、前景损坏和仪器畸变将被添加到模拟中，以生成21厘米观测天空图的完整模拟。接下来，研究人员将在这些模拟观测图上测量一系列统计数据，以表征从提高采收率信号中获得的最可靠的有用信息。在教育方面，一名本科生将在一所院校获得支持和指导，两所院校的研究生将获得支持和指导。本项目学生训练的一个重要特点是研究的跨学科性质，包括复杂的统计分析、分析和数值模拟、仪器建模和天体物理学。学生的经验也将强调实验条件和科学分析之间的相互联系。

One important new frontier of cosmology is the Epoch of Reionization (EoR), marking the time when the Universe's first luminous objects formed and the time of the final phase of cosmological formation of structure in the Universe. Most investigators seek to observe the EoR by detecting neutral hydrogen gas of the intergalactic medium (IGM) through its signature in the redshifted 21-cm spectral line. While a variety of projects are currently underway to detect the EoR signal, thermal noise will dominant the signal and will require careful statistical analysis of the observational data to infer the statistical nature of the EoR signal. Unfortunately, one of the statistical techniques employed will be to characterize power spectrum of the EoR signal even though this signal is expected to be non-Gaussian.The intent of this project is to systematically explore statistics that reach far beyond the power spectrum technique. The investigators will compute radiative transfer simulations of reionization for a wide variety of well-defined theoretical models. Expected thermal noise, foreground corruption, and instrumental distortions will next be added to the simulations to produce complete simulations of observational sky maps in 21 cm. The investigators will next measure a range of statistics on these simulated observational maps to characterize the most robust useful information obtainable from the EoR signal.Educationally, an undergraduate will receive support and mentoring at one institution, and graduate students at two institutions will receive support and mentoring. An important feature of student training in this project is the interdisciplinary nature of the research including complex statistical analysis, analytical and numerical simulations, instrumental modeling, and astrophysics. The student experience will also emphasize the interconnection between experimental conditions and scientific analysis.