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arXiv 1201.2190astro-ph.CO
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使用FastICA去除前景:LOFAR-EoR的一个实例

Foreground Removal using FastICA: A Showcase of LOFAR-EoR

Emma Chapman, Filipe B. Abdalla, Geraint Harker, Vibor Jelić, Panagiotis Labropoulos, Saleem Zaroubi, Michiel A. Brentjens, A. G. de Bruyn, L. V. E. Koopmans

摘要:

我们介绍了一种新的实现FastICA算法的模拟LOFAR EoR数据的目的是准确地消除前景和提取21厘米的再电离信号。我们发现,该方法成功地消除了前景,平均拟合误差为0.5%,并且在整个频率范围内恢复了2D和3D功率谱。我们发现,对于尺度以上的几个PSF尺度的21厘米的方差是成功地恢复,但有证据表明,噪声泄漏到重建的前景成分。我们发现,这种盲目的独立成分分析技术提供了令人鼓舞的结果,没有事先的前景假设的危险。

英文摘要:

We introduce a new implementation of the FastICA algorithm on simulated LOFAR EoR data with the aim of accurately removing the foregrounds and extracting the 21-cm reionization signal. We find that the method successfully removes the foregrounds with an average fitting error of 0.5 per cent and that the 2D and 3D power spectra are recovered across the frequency range. We find that for scales above several PSF scales the 21-cm variance is successfully recovered though there is evidence of noise leakage into the reconstructed foreground components. We find that this blind independent component analysis technique provides encouraging results without the danger of prior foreground assumptions.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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