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Get Free AccessWe present extensive photometric and spectroscopic observations of the peculiar Type Ia supernova (SN Ia) 2022vqz. It shares many similarities with the SN 2002es-like SNe Ia, such as low luminosity ($M_{B,\rm max}=-18.11\pm0.16$ mag) and moderate post-peak decline rate ($Δm_{15,B}=1.33\pm0.11$ mag). The nickel mass synthesised in the explosion is estimated as $0.20\pm0.04~{\rm M}_\odot$ from the bolometric light curve, which is obviously lower than that of normal SNe Ia. SN 2022vqz is also characterised by slowly expanding ejecta, with Si II velocities persisting around 7000 km s$^{-1}$ since 16 days before peak brightness, unique among all known SNe Ia. While all of these properties imply a lower-energy thermonuclear explosion that should leave a considerable amount of unburnt materials, the absent signature of unburnt carbon in spectra of SN 2022vqz is puzzling. A prominent early peak is clearly detected in the ATLAS $c$- and $o$-band light curves and in the ZTF $gr$-band data within days after the explosion. Possible mechanisms for the early peak are discussed, including the sub-Chandrasekhar-mass double-detonation model and interaction of SN ejecta with circumstellar material. We find that both models face some difficulties in replicating all aspects of the observed data. As an alternative, we propose a hybrid C-O-Ne white dwarf as the progenitor of SN 2022vqz; it can simultaneously reconcile the tension between low ejecta velocity and the absence of carbon. We further discuss the diversity of SN 2002es-like objects and their origin in the context of different scenarios.
Gaobo Xi, Xiaofeng Wang, Gaici Li, Jialian Liu, Shengyu Yan, Weili Lin, Jieming Zhao, Alexei V Filippenko, WeiKang Zheng, Thomas G. Brink, Yi Yang, Shuhrat Ehgamberdiev, D. O. Mirzaqulov, A. Reguitti, A. Pastorello, L. Tomasella, Yongzhi Cai, Jujia Zhang, Zhitong Li, Tianmeng Zhang, Zhihao Chen, Qichun Liu, Xiaoran Ma, Danfeng Xiang (2023). SN 2022vqz: A Peculiar Subluminous Type Ia Supernova with Prominent Early Excess Emission. , DOI: https://doi.org/10.48550/arxiv.2309.09213.
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Type
Preprint
Year
2023
Authors
24
Datasets
0
Total Files
0
Language
en
DOI
https://doi.org/10.48550/arxiv.2309.09213
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