Cosmological constraints from the <i>Planck</i> cluster catalogue with new multi-wavelength mass calibration from <i>Chandra</i> and CFHT
Bibliographic record
Abstract
We provide a new scaling relation between YSZ, the integrated Sunyaev-Zeldovich signal and M500YX, the cluster mass derived from X-ray observations, using a sample of clusters from the Planck Early Sunyaev-Zeldovich (ESZ) catalogue observed in X-rays by Chandra, and compare it to the results of the Planck collaboration obtained from XMM-Newton observations of a subsample of the ESZ. We calibrated a mass bias on a subset of the Planck cosmological cluster sample using published weak-lensing data from the Canadian Cluster Cosmology Project (CCCP) and Multi Epoch Nearby Cluster Survey (MENeaCS), for the new scaling relation as well as that from the Planck collaboration. We propose a novel method to account for selection effects and find a mass bias of (1 − b) = 0.89 ± 0.04 for the Chandra-calibrated scaling relation, and (1 − b) = 0.76 ± 0.04 for the XMM-Newton-calibrated scaling relation. We applied the scaling relations we derived to the full Planck cosmological cluster sample and obtain new constraints on the cosmological parameters. We find identical constraints regardless of the X-ray sample used, with σ8 = 0.77 ± 0.02, Ωm = 0.31 ± 0.02, and S8 ≡ σ8 √(Ωm/0.3) = 0.78 ± 0.02. We also provide constraints with a redshift evolution of the scaling relation fitted from the data instead of fixing it to the self-similar value. We find a redshift evolution significantly deviating from the self-similar value, leading to a higher value of S8 = 0.81 ± 0.02. We compare our results to those from various cosmological probes, and find that our S8 constraints are competitive with the tightest constraints from the literature. When assuming a self-similar redshift evolution, our constraints are in agreement with most late-time probes and in tension with constraints from the cosmic microwave background (CMB) primary anisotropies. When relaxing the assumption of redshift evolution and fitting it to the data, we find no significant tension with results from either late-time probes or the CMB.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".