<i>Hubble Space Telescope</i>studies of low-redshift Type Ia supernovae: evolution with redshift and ultraviolet spectral trends
Bibliographic record
Abstract
We present an analysis of the maximum light, near-ultraviolet (NUV; 2900 < λ < 5500 Å) spectra of 32 low-redshift (0.001 < z < 0.08) Type Ia supernovae (SNe Ia), obtained with the Hubble Space Telescope (HST) using the Space Telescope Imaging Spectrograph. We combine this spectroscopic sample with high-quality gri light curves obtained with robotic telescopes to measure SN Ia photometric parameters, such as stretch (light-curve width), optical colour and brightness (Hubble residual). By comparing our new data to a comparable sample of SNe Ia at intermediate redshift (0.4 < z < 0.9), we detect modest spectral evolution (3σ), in the sense that our mean low-redshift NUV spectrum has a depressed flux compared to its intermediate-redshift counterpart. We also see a strongly increased dispersion about the mean with decreasing wavelength, confirming the results of earlier surveys. We show that these trends are consistent with changes in metallicity as predicted by contemporary SN Ia spectral models. We also examine the properties of various NUV spectral diagnostics in the individual SN spectra. We find a general correlation between SN stretch and the velocity (or position) of many NUV spectral features. In particular, we observe that higher stretch SNe have larger Ca ii H&K velocities, which also correlate with host galaxy stellar mass. This latter trend is probably driven by the well-established correlation between stretch and host galaxy stellar mass. We find no significant trends between UV spectral features and optical colour. Mean spectra constructed according to whether the SN has a positive or negative Hubble residual show very little difference at NUV wavelengths, indicating that the NUV evolution and variation we identify does not directly correlate with Hubble diagram residuals. Our work confirms and strengthens earlier conclusions regarding the complex behaviour of SNe Ia in the NUV spectral region, but suggests the correlations we find are more useful in constraining progenitor models rather than improving the use of SNe Ia as cosmological probes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".