North+Lone Star Supernova Host Survey I: Local Host-Galaxy H$α$ Surface Brightness and the Hubble Residuals of Type Ia Supernovae
Bibliographic record
Abstract
We present optical integral-field unit (IFU) spectroscopy acquired with the George and Cynthia Mitchell Spectrograph on the Harlan J. Smith telescope at McDonald Observatory of 94 galaxies (0.01 < z < 0.058) that have hosted Type Ia supernovae (SNe Ia). We selected host galaxies with star-forming morphology, consistent with the criteria used by Riess et al. (2022). We measured the H$α$ surface brightness of each host galaxy within 1 kpc of the location of the supernova. Using distances from the Pantheon+ sample, we find a step in Hubble residuals compared to local H$α$ surface brightness of -0.097 $\pm$ 0.051 mag at 1.9$σ$ significance in a sample of 73 host galaxies, where SNe in environments with smaller H$α$ surface brightness are, on average, less luminous after correction for light-curve shape and color. Almost all of the SNe in our sample were discovered by targeted surveys. Using an independent sample primarily from the untargeted Nearby Supernova Factory survey, Rigault et al. (2020) found a step of 0.045 $\pm$ 0.029 mag where SNe in passive environments are instead brighter, which is in 2.4$σ$ tension with our measurement. Rigault et al. (2013) designated SNe Ia comparatively small HRs (< -0.1) and faint local H$α$ surface brightness (SB) (
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".