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Stripped-envelope core-collapse supernova ⁵⁶Ni masses: Persistently larger values than supernovae type II
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Stripped-envelope core-collapse supernova ⁵⁶Ni masses: Persistently larger values than supernovae type II
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The mass of synthesised radioactive material is an important power source for all supernova (SN) types. Anderson 2019 recently compiled literature values and obtained $^{56}$Ni distributions for different core-collapse supernovae (CC-SNe), showing that the $^{56}$Ni distribution of stripped envelope CC-SNe (SE-SNe: types IIb, Ib, and Ic) is highly incompatible with that of hydrogen rich type II SNe (SNe-II). This motivates questions on differences in progenitors, explosion mechanisms, and $^{56}$Ni estimation methods. Here, we re-estimate the nucleosynthetic yields of $^{56}$Ni for a well-observed and well-defined sample of SE-SNe in a uniform manner. This allows us to investigate whether the observed SN-II--SE-SN $^{56}$Ni separation is due to real differences between these SN types, or because of systematic errors in the estimation methods. We compiled a sample of well observed SE-SNe and measured $^{56}$Ni masses through three different methods proposed in the literature. Arnett's rule -as previously shown - gives $^{56}$Ni masses for SE-SNe that are considerably higher than SNe-II. While for the distributions calculated using both the Khatami&Kasen prescription and Tail $^{56}$Ni masses are offset to lower values than `Arnett values', their $^{56}$Ni distributions are still statistically higher than that of SNe II. Our results are strongly driven by a lack of SE-SN with low $^{56}$Ni masses (that are in addition strictly lower limits). The lowest SE-SN $^{56}$Ni mass in our sample is of 0.015M$_\odot$, below which are more than 25$\%$ of SNe II. We conclude that there exists real, intrinsic differences in the mass of synthesised radioactive material between SNe II and SE-SNe . Any proposed current or future CCSN progenitor scenario and explosion mechanism must be able to explain why and how such differences arise, or outline a yet to be fully explored bias in current SN samples.
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