SN 2017hpa: A Nearby Carbon-rich Type Ia Supernova with a Large Velocity Gradient
We present extensive, well-sampled optical and ultraviolet photometry and optical spectra of the Type Ia supernova (SN Ia) 2017hpa. The light curves indicate that SN 2017hpa is a normal SN Ia with an absolute peak magnitude of −19.12 ± 0.11 mag and a postpeak decline rate Δ m 15 ( B ) = 1.02 ± 0.07...
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Veröffentlicht in: | The Astrophysical journal 2021-03, Vol.909 (2), p.176 |
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Hauptverfasser: | , , , , , , , , , , , , , , , , , , , , , , , , , , |
Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | We present extensive, well-sampled optical and ultraviolet photometry and optical spectra of the Type Ia supernova (SN Ia) 2017hpa. The light curves indicate that SN 2017hpa is a normal SN Ia with an absolute peak magnitude of
−19.12 ± 0.11 mag and a postpeak decline rate Δ
m
15
(
B
) = 1.02 ± 0.07 mag. According to the quasi-bolometric light curve, we derive a peak luminosity of 1.25 × 10
43
erg s
−1
and a
56
Ni mass of 0.63 ± 0.02
M
⊙
. The spectral evolution of SN 2017hpa is similar to that of normal Ia supernovae (SNe Ia), while it exhibits an unusually rapid velocity evolution resembling that of SN 1991bg-like SNe Ia or the high-velocity subclass of SNe Ia, with a postpeak velocity gradient of ∼130 ± 7 km s
−1
day
−1
. Moreover, its early spectra (
t
< − 7.9 days) show a prominent C
ii
λ
6580 absorption feature, which disappeared in near-maximum-light spectra but reemerged at phases from
t
∼ + 8.7 days to
t
∼ + 11.7 days after maximum light. This implies that some unburned carbon may mix deep into the inner layer and is supported by the low C
ii
λ
6580-to-Si
ii
λ
6355 velocity ratio (∼0.81) observed in SN 2017hpa. The O
i
λ
7774 line shows a velocity distribution like that of carbon. The prominent carbon feature, the low velocity seen in carbon and oxygen, and the large velocity gradient make SN 2017hpa stand out from other normal SNe Ia and are more consistent with predictions from a violent merger of two white dwarfs. Detailed modeling is still needed to reveal the nature of SN 2017hpa. |
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ISSN: | 0004-637X 1538-4357 |
DOI: | 10.3847/1538-4357/abdeb9 |