Cross-correlating 21 cm and galaxy surveys: implications for cosmology and astrophysics
Bibliographic record
Abstract
ABSTRACT We forecast astrophysical and cosmological parameter constraints from synergies between 21 cm intensity mapping and wide-field optical galaxy surveys (both spectroscopic and photometric) over z ∼ 0–3. We focus on the following survey combinations in this work: (i) a CHIME-like and DESI-like survey in the Northern hemisphere, (ii) an LSST-like and SKA I MID-like survey, and (iii) a MeerKAT-like and DES-like survey in the Southern hemisphere. We work with the ΛCDM cosmological model having parameters {h, Ωm, ns, Ωb, σ8}, parameters vc, 0 and β representing the cut-off and slope of the H i–halo mass relation in the previously developed H i halo model framework, and a parameter Q that represents the scale dependence of the optical galaxy bias. Using a Fisher forecasting framework, we explore (i) the effects of the H i and galaxy astrophysical uncertainties on the cosmological parameter constraints, assuming priors from the present knowledge of the astrophysics, (ii) the improvements on astrophysical constraints over their current priors in the three configurations considered, and (iii) the tightening of the constraints on the parameters relative to the corresponding H i autocorrelation surveys alone.
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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 | 0.011 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".