Bibliographic record
Abstract
After an introduction of the general context of the ``standard'' cosmology, this thesis presents, how, using comparison of the apparent luminosity of nearby and distant type Ia supernovae (SNIa), it is possible to specify the geometry of the universe and perform a measurement of the principal cosmological parameters. We describe, after, how, from observations using the wide field camera CFH12K mounted on the CFHT (Canada France Hawaii Telescope, 3.6m, Hawaii) and softwares developed within our group, we were able to discover during the spring 2001 a batch of 4 distant SNIa. A similar search carried out with the CTIO (Cerro Tololo Interamerican Telescope, 4M, Chile) by our collaborators allowed the discovery of about ten additional supernovae. We present in this thesis the analyze of the 6 farthest supernovae (with redshift between 0.5 and 1.2) that were followed by the instrument WFPC2 of the Hubble Space Telescope. From these observations, we constructed their lightcurves using photometric differential analysis specific to the instrument WFPC2 that we developed during this work. The simulation of the flux of those supernovae within the observationnal instruments enabled us to construct lightcurve models and then fits of their characteristics: apparent luminosity at the time of maximum and decline rate. Finally, using the comparison of this batch to a batch of about one hundred nearby SNIa coming from the literature, we performed a measure of the cosmological parameters. We find, considering a flat universe, a reduced density of matter of 0.35 (0.15 stat) and 0.22 (0.25 stat) respectively for the supernovae with a redshift around 0.5 and around 1.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".