Exploring the cosmic 21-cm signal from the Epoch of Reionisation using the Wavelet Scattering Transform

TL;DR

This paper introduces the Wavelet Scattering Transform as a new method to analyze the non-Gaussian 21-cm signals from the Epoch of Reionisation, outperforming traditional power spectrum analysis in extracting astrophysical information.

Contribution

It presents the WST technique for 21-cm signal analysis, demonstrating its effectiveness over power spectrum methods and its robustness against foreground contamination.

Findings

WST can outperform the 3D power spectrum in constraining parameters.

Foreground removal reduces WST's constraining power by 1.5-2 times.

Higher cadence imaging improves the WST's parameter constraints.

Abstract

Detecting the cosmic 21-cm signal during the Epoch of Reionisation and Cosmic Dawn will reveal insights into the properties of the first galaxies and advance cosmological parameter estimation. Until recently, the primary focus for astrophysical parameter inference from the 21-cm signal centred on the power spectrum (PS). However, the cosmic 21-cm signal is highly non-Gaussian rendering the PS sub-optimal for characterising the cosmic signal. In this work, we introduce a new technique to analyse the non-Gaussian information in images of the 21-cm signal called the Wavelet Scattering Transform (WST). This approach closely mirrors that of convolutional neural networks with the added advantage of not requiring tuning or training of a neural network. Instead, it compresses the 2D spatial information into a set of coefficients making it easier to interpret while also providing a robust statistical description of the non-Gaussian information contained in the cosmic 21-cm signal. First, we explore the application of the WST to mock 21-cm images to gain valuable physical insights by comparing to the known behaviour from the 21-cm PS. Then we quantitatively explore the WST applied to the 21-cm signal by extracting astrophysical parameter constraints using Fisher Matrices from a realistic 1000 hr mock observation with the Square Kilometre Array. We find that: (i) the WST applied only to 2D images can outperform the 3D spherically averaged 21-cm PS, (ii) the excision of foreground contaminated modes can degrade the constraining power by a factor of ~1.5-2 with the WST and (iii) higher cadences between the 21-cm images can further improve the constraining power.