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Carbon burning and hydrodynamic mixing uncertainties in stellar models

Carbon burning and hydrodynamic mixing uncertainties in stellar models Thumbnail


Abstract

The aim of this thesis is to investigate uncertainties in the input physics of stellar models that are relevant for the evolution of stars and the related nucleosynthesis, in particular the s-process. Nuclear reaction rates and mixing prescriptions in particular can modify significantly the yields of heavy elements in stellar models. The s-process, which is a slow neutron-capture process that can occur in massive stars and asymptotic giant branch (AGB) stars, is an important driver for uncertainty studies because the output yields of heavy nuclides in these astrophysical sites are sensitive to the interior conditions and the input physics.
In this work, two uncertainties are considered. The first is the 12C + 12C nuclear reaction rate which, despite considerable experimental efforts, remains uncertain at temperatures relevant for hydrostatic carbon burning in massive stars. We show that changes to this reaction rate affect the stellar structure and nucleosynthesis of massive stars and, consequently, the final yields. A comparison of these yields with the Solar system abundances enabled us to constrain the 12C + 12C reaction rate in the relevant temperature range.
The second of these uncertainties is the treatment of convective-radiative interfaces in 1D stellar models, which are particularly important for modelling thermal pulses in AGB stars. The s-process during thermal pulses is sensitive to the treatment of mixing across convective-radiative interfaces. A possible link between full 3D hydrodynamics models of convective-radiative interfaces and 1D stellar models was investigated by considering a diffusion approximation. A technique for calculating diffusion coefficients from the output of hydrodynamics models was developed and an exploration of the diffusive approach for convective-boundary mixing is presented, along with the successes and limitations of this approach.

Publicly Available Date Mar 28, 2024

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