SN 2017hpa: A Nearby Carbon-Rich Type Ia Supernova with a Large Velocity Gradient
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 -19.120.11 mag and a post-peak decline rate \mb\ = 1.020.07 mag. According to the quasibolometric light curve, we derive a peak luminosity of 1.2510 erg s and a Ni mass of 0.630.02 . The spectral evolution of SN 2017hpa is similar to that of normal SNe Ia, while it exhibits unusually rapid velocity evolution resembling that of SN 1991bg-like SNe Ia or the high-velocity subclass of SNe Ia, with a post-peak velocity gradient of 1307 km s d. Moreover, its early spectra ( d) show prominent \CII~6580 absorption feature, which disappeared in near-maximum-light spectra but reemerged at phases from d to d after maximum light. This implies that some unburned carbon may mix deep into the inner layer, and is supported by the low \CII~6580 to \SiII~6355 velocity ratio () observed in SN 2017hpa. The \OI~7774 line shows a velocity distribution like that of carbon. The prominent carbon feature, low velocity seen in carbon and oxygen, and 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 modelling is still needed to reveal the nature of SN 2017hpa.
Keywords
Cite
@article{arxiv.2101.08512,
title = {SN 2017hpa: A Nearby Carbon-Rich Type Ia Supernova with a Large Velocity Gradient},
author = {Xiangyun Zeng and Xiaofeng Wang and Ali Esamdin and Craig Pellegrino and WeiKang Zheng and Jujia Zhang and Jun Mo and Wenxiong Li and D. Andrew Howell and Alexei V. Filippenko and Han Lin and Thomas G. Brink and Edward A. Baron and Jamison Burke and James M. DerKacy and Curtis McCully and Daichi Hiramatsu and Griffin Hosseinzadeh and Benjamin T. Jeffers and Timothy W. Ross and Benjamin E. Stahl and Samantha Stegman and Stefano Valenti and Lifan Wang and Danfeng Xiang and Jicheng Zhang and Tianmeng Zhang},
journal= {arXiv preprint arXiv:2101.08512},
year = {2021}
}