Spectral properties of MeerKLASS data

• Grant number: 24/12902-3
• Support Opportunities: Scholarships abroad - Research Internship - Doctorate
• Start date: February 26, 2025
• End date: February 12, 2026
• Field of knowledge: Physical Sciences and Mathematics - Astronomy - Extragalactic Astrophysics
• Principal Investigator: Carlos Alexandre Wuensche de Souza
• Grantee: Bruno Benedito Bizarria
• Supervisor: Philip Bull
• Host Institution: Instituto Nacional de Pesquisas Espaciais (INPE). Ministério da Ciência, Tecnologia e Inovação (Brasil). São José dos Campos , SP, Brazil
• Institution abroad: University of Manchester, England
• Associated to the scholarship: 22/16749-0 - Using cross-correlations and mode reconstruction techniques in neutral hydrogen intensity mapping for cosmological parameters' estimation, BP.DR

Abstract

Mapping the distribution of neutral hydrogen in the Universe through the intensity mapping technique has emerged as a promising tool to access baryon acoustic oscillations and place strong constraints on the nature of dark matter and dark energy. This technique competes with state-of-the-art optical galaxy surveys, with several instruments being constructed and operated with this aim. One of the most promising surveys is the MeerKAT Large Area Synoptic Survey (MeerKLASS) conducted with the MeerKAT radiotelescope. Recently, MeerKLASS reported the detection of the power spectrum of the 21-cm brightness temperature by cross-correlating its observations with galaxies from the WiggleZ catalog, placing a strong constraint on the cosmic HI density parameter ($\Omega_{\textrm{\hi}}b_{\textrm{\hi}} r$). However, spectral analysis indicates the presence of systematics in the data, lowering the signal-to-noise ratio and preventing the detection of the auto-correlation power spectrum. This project proposes to mitigate the effect of standing waves that arise due to gaps in the MeerKAT dishes, which manifest as systematics in the bandpass profile. It is expected that such mitigation will improve both the cross-correlation and auto-correlation power spectra, enabling stronger constraints on the auto-power spectrum detection.