A Detection of Cosmological 21 cm Emission from CHIME in Cross-correlation with eBOSS Measurements of the Lyman-$α$ Forest
Bibliographic record
Abstract
We report the detection of 21 cm emission at an average redshift $\bar{z} = 2.3$ in the cross-correlation of data from the Canadian Hydrogen Intensity Mapping Experiment (CHIME) with measurements of the Lyman-$α$ forest from eBOSS. Data collected by CHIME over 88 days in the $400-500$~MHz frequency band ($1.8 < z < 2.5$) are formed into maps of the sky and high-pass delay filtered to suppress the foreground power, corresponding to removing cosmological scales with $k_\parallel \lesssim 0.13\ \text{Mpc}^{-1}$ at the average redshift. Line-of-sight spectra to the eBOSS background quasar locations are extracted from the CHIME maps and combined with the Lyman-$α$ forest flux transmission spectra to estimate the 21 cm-Lyman-$α$ cross-correlation function. Fitting a simulation-derived template function to this measurement results in a $9σ$ detection significance. The coherent accumulation of the signal through cross-correlation is sufficient to enable a detection despite excess variance from foreground residuals $\sim6-10$ times brighter than the expected thermal noise level in the correlation function. These results are the highest-redshift measurement of \tcm emission to date, and set the stage for future 21 cm intensity mapping analyses at $z>1.8$.
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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 | 0.001 |
| 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 | 0.000 | 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".