干涉数据的贝叶斯角功率谱分析
Bayesian angular power spectrum analysis of interferometric data
摘要：
我们提出了一个贝叶斯角功率谱和信号图推理机，它可以适用于干涉观测的各向异性在宇宙微波背景，21厘米发射线映射的银河亮度波动，或21厘米吸收线映射的中性氢在黑暗时代。该方法使用吉布斯采样产生的角度功率谱后验和信号地图的后验的采样表示给定的一组测量的vibrations在uv平面。我们使用一个模拟的干涉CMB观测证明了这种方法的有效性，在平天近似时，适应考虑到任意覆盖的UV平面，模式模式的相关性，由于有限补丁上的观测，和异方差的可见性误差。计算要求为O（n_p log n_p），其中n_p测量探测器阵列的大小与探测器间距的比率，这意味着吉布斯采样是满足未来宇宙学任务数据分析要求的有前途的技术。
英文摘要：
We present a Bayesian angular power spectrum and signal map inference engine which can be adapted to interferometric observations of anisotropies inthe cosmic microwave background, 21 cm emission line mapping of galactic brightness fluctuations, or 21 cm absorption line mapping of neutral hydrogen in the dark ages. The method uses Gibbs sampling to generate a sampled representation of the angular power spectrum posterior and the posterior of signal maps given a set of measured visibilities in the uv-plane. We use a mock interferometric CMB observation to demonstrate the validity of this method in the flat-sky approximation when adapted to take into account arbitrary coverage of the uv-plane, mode-mode correlations due to observations on a finite patch, and heteroschedastic visibility errors. The computational requirements scale as O(n_p log n_p) where n_p measures the ratio of the size of the detector array to the inter-detector spacing, meaning that Gibbs sampling is a promising technique for meeting the data analysis requirements of future cosmology missions.
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