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The peculiar abundances of HE 1005-1439. A carbon-enhanced extremely metal-poor star contaminated with products of both s-and i-process nucleosynthesis

We performed a detailed, high-resolution spectroscopic analysis of HE 1005-1439 based on SUBARU/HDS spectra with an R ~ 50000. Abundances of ten light elements from C through Ni and twelve heavy elements Sr, Y, Ba, La, Ce, Pr, Nd, Eu, Dy, Er, Hf, and Pb were determined. We also performed a parametric-model-based analysis of the abundances of the heavy elements to understand the origin of the observed abundance pattern. For the first time, we came across an object with a surface chemical composition that exhibits contributions from both slow (s) and intermediate (i) neutron-capture nucleosynthesis. The observed abundance pattern is unique and has never been observed in any CEMP stars. The star is found to be a CEMP-s star based on the CEMP stars' classification criteria. However, the observed abundance pattern could not be explained based on theoretical s-process model predictions. On the contrary, our parametric-model based analysis clearly indicates its surface chemical composition being influenced by similar contributions from both the s- and i-process. We critically examined the observed abundances and carefully investigated the formation scenarios involving s-process and i-process that are available in literature, and we found that none of them could explain the observed abundances. We note that the variation we see in our radial velocity estimates obtained from several epochs may indicate the presence of a binary companion. Considering a binary system, we, therefore, propose a formation scenario for this object involving effective proton ingestion episodes (PIEs) triggering i-process nucleosynthesis followed by s-process asymptotic giant branch (AGB) nucleosynthesis with a few third-dredge-up (TDU) episodes in the now extinct companion AGB star. Results obtained from the parametric-model-based analysis are discussed in light of existing stellar evolutionary models.

preprint2021arXivOpen access

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