The effect of foreground mitigation strategy on EoR window recovery
The effect of foreground mitigation strategy on EoR window recovery
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DOI：
10.1093/mnras/stw161
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发表时间：
2014-08
影响因子：
4.8
通讯作者：
E. Chapman;S. Zaroubi;F. Abdalla;F. Dulwich;V. Jeli'c;B. Mort
中科院分区：
文献类型：
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作者：
E. Chapman;S. Zaroubi;F. Abdalla;F. Dulwich;V. Jeli'c;B. Mort
对于那些希望探测再电离时期（EoR）21厘米信号的人来说，消除银河系和河外前景仍然是一个重大挑战。多种方法模拟这些前景与不同程度的假设已经过试验，并显示出有前途的恢复模拟数据。然而，最近已经增加了使用傅立叶空间中的前景的预期形状来定义没有前景污染的EoR窗口的讨论。通过仅在此窗口内进行分析，可以避免前景和它们可能引入的任何统计偏差，而是通过删除这些前景。在本文中，我们讨论了前景消除和前景避免的优点和缺点。我们创建了一系列模拟与噪声水平符合当前和未来的实验，并比较了从前景避免和简化的，频率无关的前景去除模型恢复的统计宇宙学信号。我们发现，对于当前生成的实验，虽然前景避免能够在kperp > 0.6 Mpc-1时实现更好的恢复，但对于当前和未来的实验，前景去除能够在小klos处恢复更多的信号。我们还放宽了前景平滑的假设。仅对于视线变化，前景去除即使在1%的情况下也能够进行良好的信号恢复，而前景避免则会受到显着影响。我们发现，这两种方法在视线和空间变化约为0.1%的前景模型中表现良好，但在大于此的水平上，这两种方法都受到了影响。
The removal of the Galactic and extragalactic foregrounds remains a major challenge for those wishing to make a detection of the Epoch of Reionization (EoR) 21 cm signal. Multiple methods of modelling these foregrounds with varying levels of assumption have been trialled and shown promising recoveries on simulated data. Recently however there has been increased discussion of using the expected shape of the foregrounds in Fourier space to define an EoR window free of foreground contamination. By carrying out analysis within this window only, one can avoid the foregrounds and any statistical bias they might introduce by instead removing these foregrounds. In this paper, we discuss the advantages and disadvantages of both foreground removal and foreground avoidance. We create a series of simulations with noise levels in line with both current and future experiments and compare the recovered statistical cosmological signal from foreground avoidance and a simplified, frequency independent foreground removal model. We find that for current generation experiments, while foreground avoidance enables a better recovery at kperp > 0.6 Mpc-1, foreground removal is able to recover significantly more signal at small klos for both current and future experiments. We also relax the assumption that the foregrounds are smooth. For line-of-sight variations only, foreground removal is able to make a good signal recovery even at 1 per cent while foreground avoidance is compromised significantly. We find that both methods perform well for foreground models with line-of-sight and spatial variations around 0.1 per cent however at levels larger than this both methods are compromised.