Investigating the Reionization Epoch through 21\,cm and Line Intensity Mapping Experiments

TL;DR

This work addresses how to probe the Epoch of Reionization by cross-correlating 21 cm intensity maps with multi-line LIM tracers such as [CII] and CO. It combines semi-numerical excursion-set modeling for the ionization field with LIMpy-based line luminosity mappings tied to star formation, and performs Fisher-forecast analyses for next-generation SKA-low and FYST-like experiments under realistic foreground and interloper conditions. The results show that [CII]-21 cm cross-correlation can map the ionization fraction $x_e$ across redshift with 9–40$\sigma$ significance, while CO(1–0)–21 cm can yield even tighter constraints (e.g., a ~46% improvement in $x_e$ at $z\sim7.3$); joint analyses across multiple lines can break degeneracies and enable tomographic recovery of the reionization history. These findings highlight the complementary strengths of LIM and 21 cm observations, offering a path to robustly constrain both the timing and morphology of reionization and the properties of the ionizing galaxy population with upcoming facilities.

Abstract

The epoch of reionization (EoR), marking the Universe's transition from a neutral to ionized state, represents a pivotal phase for understanding the formation of the first stars and galaxies. Intensity mapping of atomic and molecular lines, such as $[\mathrm{CII}]$ and CO J-ladder transitions, across a broad redshift range is a powerful tool for investigating star formation history, metallicity, the distribution of gas and dust, and the physical conditions within galaxies. Additionally, 21\,cm line intensity mapping directly probes the neutral hydrogen content in the intergalactic medium, offering a unique window into the timing and morphology of reionization. In this study, we explore the cross-correlation between the 21\,cm signal and multi-line intensity mapping (LIM) to forecast their detectability for next-generation experiments. Our analysis emphasizes the complementary potential of these techniques to constrain parameters such as the minimum mass of ionizing sources and the ionization fraction $x_e$. Cross-correlations with LIM also enable constraints on physical properties like metal enrichment and the relationship between star formation rates and multi-line luminosities. Using mock observations from Square Kilometre Array (SKA)-low 21\,cm and Fred Young Submillimeter Telescope (FYST)-like LIM experiments, we find that the $[\mathrm{CII}]$--21\,cm cross-correlation can constrain reionization history by measuring $x_e$ across multiple redshift bins with significance levels ranging from 9 to 40$σ$. We extend our analysis to CO transitions, showing that the CO(1-0)--21\,cm cross-correlation provides competitive constraints on reionization parameters. The synergies explored here will enable robust constraints on both reionization and LIM parameters, maximizing the scientific return of current and next-generation intensity mapping experiments.

Figures (9)

• Figure 1: Schematic workflow for [CII]-21 cm and COs-21 cm cross-correlations analysis. We model [CII]/CO emissions using halo mass-to-SFR and SFR-to-luminosity scaling relations, and 21cm signals via excursion set formalism applied to ionizing photon production. Cross-correlation of the resulting intensity maps enables power spectrum forecasts. Finally, we incorporate instrumental noise, interlopers, foregrounds, and other effects to forecast the detectability of these cross-correlations and determine the constraints on the parameters of interest.
• Figure 2: Evolution of the free-electron fraction for a tanh reionization history. We illustrate the change in the ionization fraction resulting from variations in the central redshift of reionization and the width of reionization using two adjacent colorbars. The reionization history derived from the radiative transfer simulations by kulkarni2019l-reio is overplotted for comparison.
• Figure 3: A snapshot of the 21 cm brightness temperature fluctuations and [CII] intensity emission at $z \sim 7.3$. The black dots on the 21 cm panel represent the distribution of dark matter halos. For visibility purposes, we apply a beam convolution with $\theta = 1\,\mathrm{arcmin}$ to the [CII] intensity map.
• Figure 4: Left: the auto power spectrum of the 21 cm signal at redshifts 7.6, 7.3, 6.6, and 5.8 for ionization fractions of 0.35, 0.42, 0.63, and 0.91, respectively. The 21 cm power spectrum decreases with decreasing redshift as the Universe becomes more ionized, reducing the abundance of neutral hydrogen. Right: the power spectrum of [CII] line emissions at the same redshifts as the 21 cm signal. The power spectrum increases with redshift as more sources produce high-energy photons that ionize the IGM. As we integrate over all sources, the amplitude increases. For the LIM calculation, we use the Schareer20 models to generate the LIM maps.
• Figure 5: We show the cross-correlated signal between the 21 cm and [CII] line emissions at four different redshifts. The anti-correlation between these two signals reaches its maximum value when the Universe is half ionized and half neutral.