Researchers Yannic Pietschke, Anne Hutter, and Caroline Heneka, affiliated with the University of Cambridge, have published a study in the journal Monthly Notices of the Royal Astronomical Society that explores the potential of cross-correlating 21cm observations with galaxy surveys to better understand the epoch of reionization, a pivotal period in the universe’s history when the first stars and galaxies began to ionize the intergalactic medium.
The study focuses on the power of cross-correlations between 21cm observations, which detect neutral hydrogen, and galaxy surveys to reduce foreground noise and link the morphology of ionization to the galaxies causing it. The researchers used a simulation-based inference framework called EoRFlow to estimate parameters without relying on likelihood functions, a technique known as likelihood-free inference.
The team found that for a fiducial survey with a field of view of 100 square degrees, a redshift precision of 0.001, and a minimum halo mass of 10^11 solar masses, cross-power spectra yield unbiased constraints on the neutral hydrogen fraction and mean overdensity. These constraints are about 10% relative to priors and reduce posterior volumes by 20-30% compared to using 21cm auto-power alone. However, with foreground avoidance, spectroscopic redshift precision is crucial; photometric redshifts make cross-correlations uninformative.
One of the notable findings is that cross-power spectra can constrain ionizing source properties, such as the escape fraction of ionizing photons and star formation efficiency, which remain degenerate in auto-power spectra. To achieve tight constraints, the study suggests either deep surveys that detect faint galaxies with moderate foregrounds or conservative mass limits with optimistic foreground removal.
In practical terms for the energy sector, understanding the epoch of reionization and the properties of the first galaxies can provide insights into the early universe’s energy budget and the formation of the first stars and black holes. This knowledge can help energy researchers model the universe’s energy evolution more accurately and potentially inform the search for dark energy and dark matter, which are key areas of interest for understanding the universe’s energy content and dynamics.
This article is based on research available at arXiv.