New technique reveals how to read the universe's earliest ionization history
Researchers have identified a superior method to extract clues about the universe's first billion years using radio telescopes. The approach uses topological data patterns rather than traditional spectral analysis, potentially accelerating scientific discovery and informing billion-dollar investments in next-generation observatories like the Square Kilometre Array.
Originaltitel: Implicit inference of the reionization history with higher-order statistics of the 21-cm signal
ABSTRACT The Epoch of Reionization (EoR), when the first luminous sources ionized the intergalactic medium, represents a new frontier in cosmology. The Square Kilometre Array Observatory (SKAO) will offer unprecedented insights into this era through observations of the redshifted 21-cm signal, enabling constraints on the Universe’s reionization history. We investigate the information content of the average neutral hydrogen fraction ($\bar{x}_{\rm HI}$) in several Gaussian (spherical and cylindrical power spectra) and non-Gaussian (Betti numbers and bispectrum) summary statistics of the 21-cm signal. Mock 21-cm observations are generated using the AA* configuration of SKAO’s low-frequency telescope, incorporating noise levels for 100 and 1000 h. We employ a state-of-the-art implicit inference framework to learn posterior distributions of $\bar{x}_{\rm HI}$ in redshift bins centred at $z=8.0, ~ 7.2,$ and 6.5, for each statistic and noise scenario, validating the posteriors through calibration tests. Using the figure of merit to assess constraining power, we find that Betti numbers alone are on average more informative than the power spectra, while the bispectrum provides limited constraints. However, combining higher-order statistics with the cylindrical power spectrum improves the mean figure of merit by $\sim$0.25 dex ($\sim$33 per cent reduction in $\sigma (\bar{x}_{\rm HI})$). The relative contribution of each statistic varies with the stage of reionization. With SKAO observations approaching, our results show that combining power spectra with higher-order statistics can significantly increase the information retrieved from the EoR, maximizing the scientific return of future 21-cm observations.