Global properties of core-collapse supernovae in numerical simulations

The exact progenitor-remnant connection of core-collapse supernovae (CCSNe), i.e. if a star explodes, and if it leaves behind a neutron star (NS) or a black hole (BH), is not well understood yet. The understanding of CCSNe and their explosion mechanism(s) is a long standing problem that many astrophysicists tried to illuminate. The uncertainty of the explosion mechanism and the explodability also affect the prediction of the nucleosynthesis yields in the ejecta of CCSNe that contribute to the galactic chemical enrichment. In this thesis we study the explodability, explosion properties, and the ejecta of neutrino-driven CCSNe with numerical simulations. This includes the study of the dynamics and trends of CCSNe in dependence of progenitor properties. To investigate the explodability and the progenitor-remnant connection quantitatively one has to study large samples of CCSN progenitors. Even though multi-dimensional simulations provide a promising and necessary tool to study the exact nature of the possible explosion mechanisms, sophisticated three-dimensional models are computationally too expensive to be used in the analysis of large samples of progenitors. With some exceptions for the lightest progenitors of CCSNe, self-consistent numerically affordable one-dimensional simulations that incorporate detailed microphysics, general relativity and sophisticated neutrino-transport fail to explode.
The main focus of this thesis lies on the PUSH method, a parametrized framework to efficiently investigate CCSNe for large samples of progenitors in spherically symmetric simulations. By investigations of CCSNe we can determine the explodability and the nucleosynthesis yields in the ejecta of the explosions obtained for the progenitors, as well as dependencies of explosion properties on the progenitor properties. Main strengths of the presented PUSH method in comparison with other artificial methods are obtaining the mass cut directly from the simulations and the PNS as well as the electron flavor neutrino luminosities are computed self-consistent at all simulation times. No changes of the involved electron neutrino and anti-neutrino cross sections are made. To achieve successful explosions in otherwise non-exploding models in spherical symmetry, we rely on the neutrino-driven mechanism. In this mechanism of CCSNe electron neutrinos and antineutrinos are able to heat matter behind the stalled shock front in the gain region sufficiently to induce a shock revival that ultimately leads to an explosion. It has been found, that for efficient heating by neutrinos behind the shock multi-dimensional effects as convection are crucial. In our simulations we tap the energy of the $\mu-$ and $\tau-$neutrino luminosities that otherwise stream out of the system and increase the effective heating by neutrinos in regions where electron flavor neutrinos heat the matter. This enables us to successfully induce physically motivated parametrized neutrino-driven CCSNe in spherically symmetric simulations with a realistic SN equation of state (EOS).
After calibrating the PUSH method to SN~1987A for a suitable progenitor model, we proceed to explore large progenitor samples with solar metallicity. This is done by using observational properties of other CCSNe. By extending the calibration of the PUSH method with a dependency on compactness we can investigate CCSN simulations for progenitor models across the ZAMS mass range. We study large samples of progenitors with solar metallicity and discuss trends of the obtained results for explosion energy, nucleosynthesis yields and explodability. The resulting progenitor-remnant connection, the resulting prediction of the neutron star and black hole birth mass distributions that can be compared to observations are presented. In the final part of this thesis we discuss work done with the three-dimensional magnetohydrodynamics code with neutrino transport ELEPHANT and compare our parametrized spherically symmetric CCSN simulations to three-dimensional simulations.