THE IMPACT OF THE IONOSPHERE ON GROUND-BASED DETECTION OF THE GLOBAL EPOCH OF REIONIZATION SIGNAL

Abstract

The redshifted 21 cm line of neutral hydrogen (H i), potentially observable at low radio frequencies (∼50–200 MHz), is a promising probe of the physical conditions of the intergalactic medium during Cosmic Dawn and the Epoch of Reionization (EoR). The sky-averaged H i signal is expected to be extremely weak (∼100 mK) in comparison to the Galactic foreground emission (∼104 K). Moreover, the sky-averaged spectra measured by ground-based instruments are affected by chromatic propagation effects (∼tens of kelvin) originating in the ionosphere. We analyze data collected with the upgraded Broadband Instrument for Global Hydrogen Reionization Signal system deployed at the Murchison Radio-astronomy Observatory to assess the significance of ionospheric effects on the detection of the global EoR signal. The ionospheric effects identified in these data are, particularly during nighttime, dominated by absorption and emission. We measure some properties of the ionosphere, such as the electron temperature (Te ≈ 470 K at nighttime), magnitude, and variability of optical depth (τ100 MHz ≈ 0.01 and δτ ≈ 0.005 at nighttime). According to the results of a statistical test applied on a large data sample, very long integrations (∼100 hr collected over approximately 2 months) lead to increased signal-to-noise ratio even in the presence of ionospheric variability. This is further supported by the structure of the power spectrum of the sky temperature fluctuations, which has flicker noise characteristics at frequencies ≳10−5 Hz, but becomes flat below ≈10−5 Hz. Hence, we conclude that the stochastic error introduced by the chromatic ionospheric effects tends to zero in an average. Therefore, the ionospheric effects and fluctuations are not fundamental impediments preventing ground-based instruments from integrating down to the precision required by global EoR experiments, provided that the ionospheric contribution is properly accounted for in the data analysis.