Precision era of the kinetic Sunyaev-Zel'dovich effect: simulations, analytical models and observations and the power to constrain reionization
Bibliographic record
Abstract
The kinetic Sunyaev–Zel'dovich effect, which is the dominant cosmic microwave background (CMB) source at arcmin scales and ν∼ 217 GHz, probes the ionized gas peculiar momentum up to the epoch of reionization and is a sensitive measure of the reionization history. We ran high-resolution self-similar and ΛCDM hydro-simulations and built an analytical model to study this effect. Our model reproduces the ΛCDM simulation results to several per cent accuracy, passes various tests against self-similar simulations, and shows a wider range of applicability than previous analytical models. Our model in its continuous version is free of simulation limitations, such as a finite simulation box and finite resolution, and allows an accurate prediction of the kinetic SZ power spectrum, Cl. For the Wilkinson Microwave Anisotropy Probe cosmology, we find for the reionization redshift 6 < zreion < 20 and 3000 < l < 9000. The corresponding temperature fluctuation is several μK at these ranges. The dependence of Cl on the reionization history allows an accurate measurement of the reionization epoch. For the Atacama Cosmology Telescope (ACT) experiment, Cl can be measured with ∼1 per cent accuracy. Cl scales as (Ωbh)2σ4∼68. Given cosmological parameters, ACT would be able to constrain zreion with several per cent accuracy. Some multireionization scenarios degenerate in the primary CMB temperature and temperature–E polarization (TE) measurement can be distinguished with ∼ 10 σ confidence.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".