Optical and Near-infrared Observations of the Nearby SN Ia 2017cbv
Supernova (SN) 2017cbv in NGC 5643 is one of a handful of Type Ia supernovae (SNe Ia) reported to have excess blue emission at early times. This paper presents extensive BVRIYJHKs-band light curves of SN 2017cbv, covering the phase from −16 to +125 days relative to B-band maximum light. The SN 2017c...
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Veröffentlicht in: | The Astrophysical journal 2020-11, Vol.904 (1), p.14 |
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Sprache: | eng |
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Zusammenfassung: | Supernova (SN) 2017cbv in NGC 5643 is one of a handful of Type Ia supernovae (SNe Ia) reported to have excess blue emission at early times. This paper presents extensive BVRIYJHKs-band light curves of SN 2017cbv, covering the phase from −16 to +125 days relative to B-band maximum light. The SN 2017cbv reached a B-band maximum of 11.710 0.006 mag, with a postmaximum magnitude decline of Δm15(B) = 0.990 0.013 mag. The SN suffered no host reddening based on Phillips intrinsic color, the Lira-Phillips relation, and the CMAGIC diagram. By employing the CMAGIC distance modulus = 30.58 0.05 mag and assuming H0 = 72 km s−1 Mpc−1, we found that 0.73 M 56Ni was synthesized during the explosion of SN 2017cbv, which is consistent with estimates using reddening- and distance-free methods via the phases of the secondary maximum of the near-IR- (NIR-) band light curves. We also present 14 NIR spectra from −18 to +49 days relative to the B-band maximum light, providing constraints on the amount of swept-up hydrogen from the companion star in the context of the single degenerate progenitor scenario. No Paβ emission feature was detected from our postmaximum NIR spectra, placing a hydrogen mass upper limit of 0.1 M . The overall optical/NIR photometric and NIR spectral evolution of SN 2017cbv is similar to that of a normal SN Ia, even though its early evolution is marked by a flux excess not seen in most other well-observed normal SNe Ia. We also compare the exquisite light curves of SN 2017cbv with some Mch delayed detonation models and sub-Mch double detonation models. |
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ISSN: | 0004-637X 1538-4357 |
DOI: | 10.3847/1538-4357/abba82 |