Impacts and Statistical Mitigation of Missing Data on the 21cm Power Spectrum: A Case Study with the Hydrogen Epoch of Reionization Array

TL;DR

This paper investigates how missing data and systematic effects impact 21cm power spectrum measurements, demonstrating that inpainting can mitigate foreground contamination and improve analysis accuracy in noisy RFI environments.

Contribution

It introduces a statistical framework that incorporates inpainting of missing data into power spectrum estimation, enhancing robustness against systematic effects and RFI.

Findings

Inpainting reduces foreground ringing caused by missing data.

Systematic effects combined with missing data significantly contaminate the power spectrum.

The framework improves power spectrum analysis for real observational data.

Abstract

The precise characterization and mitigation of systematic effects is one of the biggest roadblocks impeding the detection of the fluctuations of cosmological 21cm signals. Missing data in radio cosmological experiments, often due to radio frequency interference (RFI), poses a particular challenge to power spectrum analysis as it could lead to the ringing of bright foreground modes in Fourier space, heavily contaminating the cosmological signals. Here we show that the problem of missing data becomes even more arduous in the presence of systematic effects. Using a realistic numerical simulation, we demonstrate that partially flagged data combined with systematic effects can introduce significant foreground ringing. We show that such an effect can be mitigated through inpainting the missing data. We present a rigorous statistical framework that incorporates the process of inpainting missing data into a quadratic estimator of the 21cm power spectrum. Under this framework, the uncertainties associated with our inpainting method and its impact on power spectrum statistics can be understood. These results are applied to the latest Phase II observations taken by the Hydrogen Epoch of Reionization Array, forming a crucial component in power spectrum analyses as we move toward detecting 21cm signals in the ever more noisy RFI environment.