The Pantheon Sample Analysis of Cosmological Constraints under New Models
Bibliographic record
Abstract
In this paper, the cosmological parameters are determined by applying six cosmological models to fit the magnitude-redshift relation of the Pantheon Sample consisting of 1048 Type Ia supernovae (SNe Ia) in the range of $0.01 < z < 2.26$. Apart from the well-known flat $Λ$CDM model as well as other models that have been broadly studied, this paper includes two new models, the $ow$CDM model and the $ow_{0}w_{a}$CDM model, to fully evaluate the correlations between the cosmological parameters by performing the MCMC algorithm and to explore the geometry and mass content of the Universe. Combining the measurements of the baryon acoustic oscillation (BAO) and the cosmic microwave background (CMB) with the SNe Ia constraints, the matter density parameter $Ω_\mathrm{M} = 0.328^{+0.018}_{-0.026}$, the curvature of space parameter $Ω_{k} = 0.0045^{+0.0666}_{-0.0741}$, and the dark energy equation of state parameter $w = -1.120^{+0.143}_{-0.185}$ are measured for the $ow$CDM model. When it comes to the $ow_{0}w_{a}$CDM model, if the parameter $w$ is allowed to evolve with the redshift as $w = w_{0} + w_{a}\left(1-a\right)$, the cosmological parameters are found to be $Ω_\mathrm{M} = 0.344^{+0.018}_{-0.027}$, $Ω_{k} = 0.0027^{+0.0665}_{-0.0716}$, $w_{0} = -0.739^{+0.336}_{-0.378}$, and $w_{a} = -0.812^{+0.750}_{-0.678}$. The $ow$CDM model and the $ow_{0}w_{a}$CDM model are able to fit the Pantheon Sample consistently well with $χ_ν^{2} = 0.994$ and $χ_ν^{2} = 1.008$, but the parameters $w_{0}$ and $w_{a}$ are not well constrained in both models. Meanwhile, the flat $Λ$CDM model is found to fit poorly for $z > 0.5$ high-redshift SNe Ia data with $χ_ν^{2} = 0.792$ compared to the $w_{0}w_{a}$CDM model with $χ_ν^{2} = 0.971$ and the $ow_{0}w_{a}$CDM model with $χ_ν^{2} = 0.824$.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| 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) | 0.006 | 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".