The Cosmic Reionization History as Revealed by the CMB Doppler--21-cm Correlation
arXiv:astro-ph/0512010 · doi:10.1086/504888
Abstract
We show that the epoch(s) of reionization when the ionization fraction of the universe is about half can be determined by correlating Cosmic Microwave Background (CMB) temperature maps with 21-cm line maps at degree scales (). During reionization peculiar motion of free electrons induces the Doppler anisotropy of the CMB, while density fluctuations of neutral hydrogen induce the 21-cm line anisotropy. In our simplified model of inhomogeneous reionization, a positive correlation arises as the universe reionizes whereas a negative correlation arises as it recombines; thus, the sign of the correlation provides information on the reionization history which cannot be obtained by presently. The signal comes mainly from large scales (k~0.01 Mpc^-1) where linear perturbation theory is valid and complexity due to patchy reionization is averaged out. Since the Doppler signal comes from ionized regions and the 21-cm comes from neutral ones, the correlation has a well-defined peak(s) in redshift when the ionization fraction of the universe is about half. Furthermore, the cross-correlation is much less sensitive to systematic errors, especially foreground emission, than the auto-correlation of 21-cm lines: this is analogous to the temperature-polarization correlation of the CMB being more immune to systematic errors than the polarization-polarization. Therefore, we argue that the Doppler-21cm correlation provides a robust measurement of the 21-cm anisotropy, which can also be used as a diagnostic tool for detected signals in the 21-cm data -- detection of the cross-correlation provides the strongest confirmation that the signal is of cosmological origin. We show that the Square Kilometer Array can easily measure the predicted correlation signal for 1~year of survey observation.
arXiv comment14 pages, 5 figures, accepted for publication in ApJ; substantial revisions to correct the treatment of bias and reflect the accepted version
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