The Application of Continuous Wavelet Transform Based Foreground Subtraction Method in 21 cm Sky Surveys

Abstract

We propose a continuous wavelet transform based non-parametric foreground subtraction method for the detection of redshifted 21 cm signal from the epoch of reionization. This method works based on the assumption that the foreground spectra are smooth in frequency domain, while the 21 cm signal spectrum is full of saw-tooth-like structures, thus their characteristic scales are significantly different. We can distinguish them in the wavelet coefficient space easily and perform the foreground subtraction. Compared with the traditional spectral fitting based method, our method is more tolerant to complex foregrounds. Furthermore, we also find that when the instrument has uncorrected response error, our method can also work significantly better than the spectral fitting based method. Our method can obtain similar results with the Wp smoothing method, which is also a non-parametric method, but our method consumes much less computing time.

Accepted by ApJ

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• 21-cm signature of the first sources in the Universe: Prospects of detection with SKA
• Deep learning approach for identification of HII regions during reionization in 21-cm observations -- II. foreground contamination
• Comparisons between fast algorithms for the continuous wavelet transform and applications in cosmology: the 1D case
• Continuous wavelet analysis of matter clustering using the Gaussian-derived wavelet
• The continuous wavelet derived by smoothing function and its application in cosmology