Correlation-based Beam Calibration of 21cm Intensity Mapping

TL;DR

This paper introduces a new correlation-based method for calibrating frequency-dependent beam variations in 21cm intensity mapping, improving foreground removal accuracy in real-world data scenarios.

Contribution

The paper presents a novel internal cross-correlation technique for beam calibration that outperforms traditional methods in simulated datasets with frequency fluctuations.

Findings

Significant improvement in beam calibration accuracy

Enhanced foreground removal in simulated intensity mapping data

Method demonstrates robustness against frequency-dependent fluctuations

Abstract

Foreground removal presents a significant obstacle in both current and forthcoming intensity mapping surveys. While numerous techniques have been developed that show promise in simulated datasets, their efficacy often diminishes when applied to real-world data. A primary issue is the frequency-dependent variations in the instrumental response. In this paper, we propose a novel approach utilizing the internal cross-correlation among different frequencies to calibrate the beam's frequency fluctuations. Using a simulated dataset that incorporates frequency-dependent random fluctuations into the beam model, we illustrate that our method can achieve considerable improvements over traditional techniques. Our results represent a step forward in enhancing the precision and reliability of foreground removal in intensity mapping surveys.