The multi-frequency angular power spectrum in parameter studies of the cosmic 21-cm signal

TL;DR

This paper demonstrates that the multi-frequency angular power spectrum (MAPS) provides significantly more accurate parameter constraints than the traditional spherically averaged power spectrum (SAPS) in 21-cm cosmology, especially considering the light-cone effect.

Contribution

The study introduces the use of MAPS for parameter estimation in 21-cm signals, showing it outperforms SAPS by approximately a factor of two in constraint precision.

Findings

MAPS yields twice as stringent parameter constraints as SAPS.

The advantage of MAPS persists even with instrumental noise.

MAPS aligns better with the properties of the 21-cm signal under the light-cone effect.

Abstract

The light-cone effect breaks the periodicity and statistical homogeneity (ergodicity) along the line-of-sight direction of cosmological emission/absorption line surveys. The spherically averaged power spectrum (SAPS), which by definition assumes ergodicity and periodicity in all directions, can only quantify some of the second-order statistical information in the 3D light-cone signals and therefore gives a biased estimate of the true statistics. The multi-frequency angular power spectrum (MAPS), by extracting more information from the data, does not rely on these assumptions. It is therefore better aligned with the properties of the signal. We have compared the performance of the MAPS and SAPS metrics for parameter estimation for a mock 3D light-cone observation of the 21-cm signal from the Epoch of Reionization. Our investigation is based on a simplified 3-parameter 21cmFAST model. We find that the MAPS produces parameter constraints which are a factor of $\sim 2$ more stringent than when the SAPS is used. The significance of this result does not change much even in the presence of instrumental noise expected for 128 hours of SKA-Low observations. Our results therefore suggest that a parameter estimation framework based on the MAPS metric would yield superior results over one using the SAPS metric.