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Abstract We present the largest and most homogeneous collection of near-infrared (NIR) spectra of Type Ia supernovae (SNe Ia): 339 spectra of 98 individual SNe obtained as part of the Carnegie Supernova Project-II. These spectra, obtained with the FIRE spectrograph on the 6.5 m Magellan Baade telescope, have a spectral range of 0.8–2.5μm. Using this sample, we explore the NIR spectral diversity of SNe Ia and construct a template of spectral time series as a function of the light-curve-shape parameter, color stretchsBV. Principal component analysis is applied to characterize the diversity of the spectral features and reduce data dimensionality to a smaller subspace. Gaussian process regression is then used to model the subspace dependence on phase and light-curve shape and the associated uncertainty. Our template is able to predict spectral variations that are correlated withsBV, such as the hallmark NIR features: Mgiiat early times and theH-band break after peak. Using this template reduces the systematic uncertainties inK-corrections by ∼90% compared to those from the Hsiao template. These uncertainties, defined as the meanK-correction differences computed with the color-matched template and observed spectra, are on the level of 4 × 10−4mag on average. This template can serve as the baseline spectral energy distribution for light-curve fitters and can identify peculiar spectral features that might point to compelling physics. The results presented here will substantially improve future SN Ia cosmological experiments, for both nearby and distant samples.
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This content will become publicly available on February 1, 2026
Can Well-sampled Phase Curves Be Used to Infer Asteroid Spectral Features?
Abstract The relationship of an asteroid's reduced magnitude to its phase has a long history of study. Included in this history have been efforts to study the correlation between these parameters and spectral type. However, these efforts often suffer from the inclusion of only a few asteroids, missing phase curve data, uncorrected rotational or apparitional aberrations, and other issues. In this paper, we build upon previous approaches and address these issues. Broadly, this paper is split into two parts. The first is primarily concerned with carefully deriving phase curve parameters using a combined data set from several different sources, including observations from Gaia, the Transiting Exoplanet Survey Satellite, Palomar Transient Factory, Asteroid Terrestrial-impact Last Alert System, and Asteroid Lightcurve Data Exchange Format database using an ellipsoidal model that can correct for rotational and apparitional effects. The second concerns itself with making predictions on that data set and quantifying what can and cannot be inferred from phase parameters, both as a function of the phase curve parameterization chosen and as a function of the chosen model. We find that, while individual spectral classes remain hard to infer from the phase curves, broader statements on the presence of absorption features can dependably be made.
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- Award ID(s):
- 2206194
- PAR ID:
- 10630394
- Publisher / Repository:
- Planetary Science Journal
- Date Published:
- Journal Name:
- The Planetary Science Journal
- Volume:
- 6
- Issue:
- 2
- ISSN:
- 2632-3338
- Page Range / eLocation ID:
- 40
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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