来自宇宙微波背景干涉观测的弦信号的压缩传感重建
Compressed sensing reconstruction of a string signal from interferometric observations of the cosmic microwave background
摘要：
我们提出了一个算法重建的信号诱导宇宙弦的宇宙微波背景（CMB），从无线电干涉数据在弧分分辨率。无线电干涉测量提供了弦信号的不完整和有噪声的傅立叶测量，由于Kaiser-Stebbins（KS）效应，弦信号表现出稀疏或可压缩的梯度幅度。在这种情况下，压缩感知的通用框架自然适用于解决相应的逆问题。我们的算法特别利用了现实模拟的基础上拟合的信号的先验统计分布的模型。增强的性能相对于标准的CLEAN算法证明了在噪声条件下，包括初级和次级CMB各向异性的模拟观测。
英文摘要：
We propose an algorithm for the reconstruction of the signal induced by cosmic strings in the cosmic microwave background (CMB), from radio-interferometric data at arcminute resolution. Radio interferometry provides incomplete and noisy Fourier measurements of the string signal, which exhibits sparse or compressible magnitude of the gradient due to the Kaiser-Stebbins (KS) effect. In this context the versatile framework of compressed sensing naturally applies for solving the corresponding inverse problem. Our algorithm notably takes advantage of a model of the prior statistical distribution of the signal fitted on the basis of realistic simulations. Enhanced performance relative to the standard CLEAN algorithm is demonstrated by simulated observations under noise conditions including primary and secondary CMB anisotropies.
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