High redshift galaxies : measurements and cosmological constraints
Bibliographic record
Abstract
This thesis focuses on the measure of galaxy redshifts and their cosmological applications. This work is conducted within the context of the standard cosmological model, for which we explain the principle as well as its limitations. In particular we recall that dark matter and dark energy remain the main unsolved questions that motivates present and future cosmological surveys. Considering that photometric redshifts are solely capable to be measured for millions of galaxies, we show why they are essential to modern cosmology and how to estimate values as precise as 1–3%. We applied this method to the Canada-France-Hawaii Legacy Survey (CFHTLS) and we carefully estimated statistical and systematic uncertainties. We used these photometric redshift catalogues to measure the galaxy clustering in the CFHTLS wide. The numerous objects in our sample allowed us to construct volume-limited samples. We studied several galaxy populations including blue and red galaxies for which we found a different clustering amplitude, red galaxies being more clustered than blue ones. We modeled the clustering by the Halo Occupation Distribution model (HOD) and found a good agreement with the data. We observed that host haloes are more massive for more luminous galaxies as well as for red galaxies.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".