SNLS Spectroscopy: Testing for Evolution in Type Ia Supernovae
Bibliographic record
Abstract
Aims: We present a quantitative study of a new data set of high redshift Type Ia supernovae spectra, observed at the Gemini telescopes during the first 34 months of the Supernova Legacy Survey. During this time 123 supernovae candidates were observed, of which 87 have been identified as SNe Ia at a median redshift of z=0.720. Spectra from the entire second year of the survey and part of the third year (59 total SNe candidates with 46 confirmed SNe Ia) are published here for the first time. The spectroscopic measurements made on this data set are used determine if these distant SNe comprise a population similar to those observed locally. Methods: Rest-frame equivalent width and ejection velocity measurements are made on four spectroscopic features. Corresponding measurements are presented for a set of 167 spectra from 24 low-z SNe Ia from the literature. Results: We show that there exists a sample at high redshift with properties similar to nearby SNe. No significant difference was found between the distributions of measurements at low and high redsift for three of the features. The fourth feature displays a possible difference that should be investigated further. Correlations between Type Ia SNe properties and host galaxy morphology were also found to be similar at low and high z, and within each host galaxy class we see no evidence for redshift-evolution in SN properties. A new correlation between SNe Ia peak magnitude and the equivalent width of SiII absorption is presented. We demonstrate that this correlation reduces the scatter in SNe Ia luminosity distances in a manner consistent with the lightcurve shape-luminosity corrections that are used for Type Ia SNe cosmology. Conclusions: We show that this new sample of SNLS SNe Ia has spectroscopic properties similar to nearby objects. (Abridged)
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".