Constraining the Neutral Hydrogen Fraction from SKA Simulated Observation using a Double-Gaussian Decomposition Technique

TL;DR

This paper introduces a new double-Gaussian decomposition technique to accurately estimate the neutral hydrogen fraction during the Epoch of Reionization from SKA simulated data, providing a robust and interpretable analysis method.

Contribution

The paper presents a novel, model-independent statistical method using double-Gaussian decomposition to extract the neutral hydrogen fraction from SKA intensity maps.

Findings

The double-Gaussian model fits the pixel histogram data well.

The derived x_HI values decrease across redshift bins, indicating reionization.

Results are consistent with the simulated data.

Abstract

The Epoch of Reionization (EoR) is a unique phase in cosmic history, marked by the ionization of neutral hydrogen by the first luminous sources. The global neutral hydrogen fraction (x_HI) is a key observable for probing this era. This paper presents a novel, statistically robust method to extract the evolution of x_HI from the challenging noise-dominated data from the Square Kilometre Array (SKA) Data Challenge 3b. Our approach is based on a key physical insight: the pixel value distribution in SKA intensity maps is a mixture of signals from ionized and neutral regions. We model this distribution as a superposition of two Gaussian components-one fixed at zero representing noise and ionized bubbles, and a second, offset Gaussian tracing the neutral hydrogen signal. We perform this decomposition on data grouped into three redshift bins. The double-Gaussian model provides an excellent fit to the pixel histogram data. The derived x_HI values show a clear decreasing trend across the three redshift bins, consistent with a progressing reionization process. And the results are consistent with the provided simulation data. This method offers a powerful, model-independent, and fully interpretable way for measuring x_HI from 21 cm data, demonstrating significant potential for application to future SKA observations.