Stripped-envelope core-collapse supernova 56Ni masses: Persistently larger values than supernovae type II

Context. The mass of synthesised radioactive material is an important power source for all supernova (SN) types. In addition, the difference of Ni-56 yields statistics are relevant to constrain progenitor paths and explosion mechanisms.Aims. Here, we re-estimate the nucleosynthetic yields of Ni-56 for a well-observed and well-defined sample of stripped-envelope SNe (SE-SNe) in a uniform manner. This allows us to investigate whether the observed hydrogen-rich-stripped-envelope (SN II-SE SN) Ni-56 separation is due to real differences between these SN types or because of systematic errors in the estimation methods.Methods. We compiled a sample of well-observed SE-SNe and measured Ni-56 masses through three different methods proposed in the literature: first, the classic "Arnett rule"; second the more recent prescription of Khatami & Kasen (2019, ApJ, 878, 56) and third using the tail luminostiy to provide lower limit Ni-56 masses. These SE-SN distributions were then compared to those compiled in this article.Results. Arnett's rule, as previously shown, gives Ni-56 masses for SE-SNe that are considerably higher than SNe II. While for the distributions calculated using both the Khatami & Kasen (2019, ApJ, 878, 56) prescription and Tail Ni-56 masses are offset to lower values than "Arnett values", their Ni-56 distributions are still statistically higher than that of SNe II. Our results are strongly driven by a lack of SE-SN with low Ni-56 masses, that are, in addition, strictly lower limits. The lowest SE-SN Ni-56 mass in our sample is of 0.015 M-circle dot, below which are more than 25% of SNe II.Conclusions. We conclude that there exist real, intrinsic differences in the mass of synthesised radioactive material between SNe II and SE-SNe (types IIb, Ib, and Ic). Any proposed current or future CC SN progenitor scenario and explosion mechanism must be able to explain why and how such differences arise or outline a bias in current SN samples yet to be fully explored.