Dissemin is shutting down on January 1st, 2025

Published in

American Astronomical Society, Astrophysical Journal, 2(909), p. 176, 2021

DOI: 10.3847/1538-4357/abdeb9

Links

Tools

Export citation

Search in Google Scholar

SN 2017hpa: A Nearby Carbon-rich Type Ia Supernova with a Large Velocity Gradient

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

Full text: Download

Red circle
Preprint: archiving forbidden
Red circle
Postprint: archiving forbidden
Green circle
Published version: archiving allowed
Data provided by SHERPA/RoMEO

Abstract

Abstract 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 Δm 15(B) = 1.02 ± 0.07 mag. According to the quasi-bolometric light curve, we derive a peak luminosity of 1.25 × 1043 erg s−1 and a 56Ni 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 λ6580 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 λ6580-to-Si ii λ6355 velocity ratio (∼0.81) observed in SN 2017hpa. The O i λ7774 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.