Advancing Nucleosynthesis in Self-consistent, Multidimensional Models of Core-Collapse Supernovae

TL;DR

This paper explores the limitations of current supernova models in accurately simulating nucleosynthesis, emphasizing the need for improved methods to handle detailed nuclear composition evolution.

Contribution

The study analyzes uncertainties in post-processing nucleosynthesis calculations and discusses implications for advancing multidimensional supernova models.

Findings

Tracer particle resolution affects nucleosynthesis accuracy.

Uncertainties in expansion timescales influence composition predictions.

Determining the mass-cut impacts nucleosynthesis outcomes.

Abstract

We investigate core-collapse supernova (CCSN) nucleosynthesis in polar axisymmetric simulations using the multidimensional radiation hydrodynamics code CHIMERA. Computational costs have traditionally constrained the evolution of the nuclear composition in CCSN models to, at best, a 14-species $\alpha$-network. Such a simplified network limits the ability to accurately evolve detailed composition, neutronization and the nuclear energy generation rate. Lagrangian tracer particles are commonly used to extend the nuclear network evolution by incorporating more realistic networks in post-processing nucleosynthesis calculations. Limitations such as poor spatial resolution of the tracer particles, estimation of the expansion timescales, and determination of the "mass-cut" at the end of the simulation impose uncertainties inherent to this approach. We present a detailed analysis of the impact of these uncertainties on post-processing nucleosynthesis calculations and implications for future models.