Search

The cosmological 21 cm signal is one of the most promising avenues to study the Epoch of Reionization. One class of experiments aiming to detect this signal is global signal experiments measuring the sky-averaged 21 cm brightness temperature as a function of frequency. A crucial step in the interpretation and analysis of such measurements is separating foreground contributions from the remainder of the signal, requiring accurate models for both components. Current models for the signal (non-foreground) component, which may contain cosmological and systematic contributions, are incomplete and unable to capture the full signal. We propose two new methods for extracting this component from the data: First, we employ a foreground-orthogonal Gaussian Process to extract the part of the signal that cannot be explained by the foregrounds. Secondly, we use a FlexKnot parametrization to model the full signal component in a free-form manner, not assuming any particular shape or functional form. This method uses Bayesian model selection to find the simplest signal that can explain the data. We test our methods on both, synthetic data and publicly available EDGES low-band data. We find that the Gaussian Process can clearly capture the foreground-orthogonal signal component of both data sets. The FlexKnot method correctly recovers the full shape of the input signal used in the synthetic data and yields a multimodal distribution of different signal shapes that can explain the EDGES observations. [ABSTRACT FROM AUTHOR]

The first billion years of cosmic history remains largely unobserved. We demonstrate, using a novel machine learning technique, how combining upper limits on the spatial fluctuations in the 21-cm signal with observations of the sky-averaged 21-cm signal from neutral hydrogen can improve our understanding of this epoch. By jointly analysing data from the Shaped Antenna measurement of the background RAdio Spectrum (SARAS3, redshift z ≈ 15−25) and limits from the Hydrogen Epoch of Reionization Array (HERA, z ≈ 8 and 10), we show that such a synergetic analysis provides tighter constraints on the astrophysics of galaxies 200 million years after the big bang than can be achieved with the individual data sets. Although our constraints are weak, this is the first time data from a sky-averaged 21-cm experiment and power spectrum experiment have been analysed together. In synergy, the two experiments leave only |$64.9^{+0.3}_{-0.1}$|  per cent of the explored broad theoretical parameter space to be consistent with the joint data set, in comparison to |$92.3^{+0.3}_{-0.1}$|  per cent for SARAS3 and |$79.0^{+0.5}_{-0.2}$|  per cent for HERA alone. We use the joint analysis to constrain star formation efficiency, minimum halo mass for star formation, X-ray luminosity of early emitters, and the radio luminosity of early galaxies. The joint analysis disfavours at 68 per cent confidence a combination of galaxies with X-ray emission that is ≲33 and radio emission that is ≳32 times as efficient as present day galaxies. We disfavour at 95 per cent confidence scenarios in which power spectra are ≥126 mK2 at z  = 25 and the sky-averaged signals are ≤−277 mK. [ABSTRACT FROM AUTHOR]