Extrapolation of Type Ia Supernova Spectra into the Near-infrared Using Principal Component Analysis

Anthony Burrow, E. Baron, Christopher R. Burns,Eric Y. Hsiao,Jing Lu,Chris Ashall,Peter J. Brown,James M. DerKacy, G. Folatelli,Lluís Galbany, P. Hoeflich,Kevin Krisciunas,N. Morrell, M. M. Phillips, Benjamin J. Shappee,Maximilian D. Stritzinger, Nicholas B. Suntzeff

The Astrophysical Journal(2024)

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摘要
We present a method of extrapolating the spectroscopic behavior of Type Ia supernovae (SNe Ia) in the near-infrared (NIR) wavelength regime up to 2.30 μ m using optical spectroscopy. Such a process is useful for accurately estimating K-corrections and other photometric quantities of SNe Ia in the NIR. A principal component analysis is performed on data consisting of Carnegie Supernova Project I & II optical and NIR FIRE spectra to produce models capable of making these extrapolations. This method differs from previous spectral template methods by not parameterizing models strictly by photometric light-curve properties of SNe Ia, allowing for more flexibility of the resulting extrapolated NIR flux. A difference of around −3.1% to −2.7% in the total integrated NIR flux between these extrapolations and the observations is seen here for most test cases including Branch core-normal and shallow-silicon subtypes. However, larger deviations from the observation are found for other tests, likely due to the limited high-velocity and broad-line SNe Ia in the training sample. Maximum-light principal components are shown to allow for spectroscopic predictions of the color-stretch light-curve parameter, s _BV , within approximately ±0.1 units of the value measured with photometry. We also show these results compare well with NIR templates, although in most cases the templates are marginally more fitting to observations, illustrating a need for more concurrent optical+NIR spectroscopic observations to truly understand the diversity of SNe Ia in the NIR.
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Type Ia supernovae
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