Multipole expansion for 21 cm intensity mapping power spectrum: Forecasted cosmological parameters estimation for the SKA observatory
Bibliographic record
Abstract
ABSTRACT The measurement of the large-scale distribution of neutral hydrogen in the late Universe, obtained with radio telescopes through the hydrogen 21 cm line emission, has the potential to become a key cosmological probe in the upcoming years. We explore the constraining power of 21 cm intensity mapping observations on the full set of cosmological parameters that describe the ΛCDM model. We assume a single-dish survey for the SKA Observatory and simulate the 21 cm linear power spectrum monopole and quadrupole within six redshift bins in the range $z$ = 0.25–3. Forecasted constraints are computed numerically through Markov Chain Monte Carlo techniques. We extend the sampler CosmoMC by implementing the likelihood function for the 21 cm power spectrum multipoles. We assess the constraining power of the mock data set alone and combined with Planck 2018 CMB observations. We find that 21 cm multipoles observations alone are enough to obtain constraints on the cosmological parameters comparable with other probes. Combining the 21 cm data set with CMB observations results in significantly reduced errors on all the cosmological parameters. The strongest effect is on Ωch2 and H0, for which the error is reduced by almost a factor four. The percentage errors we estimate are $\sigma _{\Omega _ch^2} = 0.25~{{\ \rm per\ cent}}$ and $\sigma _{H_0} = 0.16~{{\ \rm per\ cent}}$, to be compared with the Planck only results $\sigma _{\Omega _ch^2} = 0.99~{{\ \rm per\ cent}}$ and $\sigma _{H_0} = 0.79~{{\ \rm per\ cent}}$. We conclude that 21 cm SKAO observations will provide a competitive cosmological probe, complementary to CMB and, thus, pivotal for gaining statistical significance on the cosmological parameters constraints, allowing a stress test for the current cosmological model.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".