Simulations of ionospheric refraction on radio interferometric data

TL;DR

This paper presents SIVIO, a simulation tool for modeling ionospheric effects on low-frequency radio interferometric data, aiding in the mitigation of ionospheric contamination for Epoch of Reionisation observations.

Contribution

The paper introduces SIVIO, a novel software for simulating ionospheric effects on radio interferometry data, enabling better understanding and correction of ionospheric distortions in EoR studies.

Findings

Simulated data accurately reproduces dispersive ionospheric effects.

Spatial structure of ionosphere can be reconstructed from source offsets.

Simulation informs strategies to mitigate ionospheric contamination.

Abstract

The Epoch of Reionisation (EoR) is the period within which the neutral universe transitioned to an ionised one. This period remains unobserved using low-frequency radio interferometers which target the 21 cm signal of neutral hydrogen emitted in this era. The Murchison Widefield Array (MWA) radio telescope was built with the detection of this signal as one of its major science goals. One of the most significant challenges towards a successful detection is that of calibration, especially in the presence of the Earth's ionosphere. By introducing refractive source shifts, distorting source shapes and scintillating flux densities, the ionosphere is a major nuisance in low-frequency radio astronomy. We introduce SIVIO, a software tool developed for simulating observations of the MWA through different ionospheric conditions estimated using thin screen approximation models and propagated into the visibilities. This enables us to directly assess the impact of the ionosphere on observed EoR data and the resulting power spectra. We show that the simulated data captures the dispersive behaviour of ionospheric effects. We show that the spatial structure of the simulated ionospheric media is accurately reconstructed either from the resultant source positional offsets or from parameters evaluated during the data calibration procedure. In turn, this will inform on the best strategies of identifying and efficiently eliminating ionospheric contamination in EoR data moving into the Square Kilometre Array era.