The Cosmic Reionization History as Revealed by the Cosmic Microwave Background Doppler–21 cm Correlation
Bibliographic record
Abstract
We show that the epoch(s) of reionization when the average ionization fraction of the universe is about half can be determined by correlating CMB temperature maps with 21 cm line maps at degree scales ( l ~ 100). 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 the universe recombines; thus, the sign of the correlation provides information on the reionization history that cannot be obtained by present means. The signal comes mainly from large scales ( k ~ 10 -2 Mpc -1 ) where linear perturbation theory is still 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 average ionization fraction of the universe is about half. Furthermore, the cross-correlation is much less sensitive to systematic errors, especially foreground emission, than the autocorrelation 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-21 cm 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 detected signal is of cosmological origin. We show that the Square Kilometer Array can easily measure the predicted correlation signal for 1 yr of survey observation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".