A Method for 21cm Power Spectrum Estimation in the Presence of Foregrounds

Mathematics – Logic

Scientific paper

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Scientific paper

In coming years, 21cm tomography has the potential to probe the Epoch of Reionization, the preceding Dark Ages, and fundamental physics with unprecedented levels of accuracy. Before this potential can be realized, however, 21 cm tomography will have to deal with the issue of foreground contamination. We present a unified matrix formalism for performing foreground cleaning and power spectrum estimation in redshifted 21 cm tomography experiments. We show that the traditional cleaning method of subtracting low-order polynomials from foreground spectra can lead to substantial mode-mixing and biases in the power spectrum, and that an inverse variance weighting of foregrounds eliminates these problems. The inverse variance method can be intuitively understood to be a high-pass filter in the line-of-sight direction, and the resulting post-subtraction power spectrum error bars are smaller than those obtained by traditional methods. This reduction of power spectrum errors will aid low-frequency radio arrays in their quest to obtain the tightest constraints on cosmological parameters as well as on reionization astrophysics.

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