The Essential Character of the Neutrino Mechanism of Core-Collapse Supernova Explosions

TL;DR

This paper introduces a simple, robust criterion based on the maximum fractional ram pressure jump at the silicon/oxygen interface to predict the explodability of massive stars in core-collapse supernovae, validated against detailed 2D simulations.

Contribution

It presents a new, easy-to-implement explosion condition derived from stellar density profiles that accurately predicts supernova outcomes without detailed simulations.

Findings

The maximum ram pressure jump predicts ~90% of explosion outcomes.

The criterion is most accurate at silicon/oxygen interface accretion.

The method outperforms existing simple explosion predictors.

Abstract

Calibrating with detailed 2D core-collapse supernova simulations, we derive a simple core-collapse supernova explosion condition based solely upon the terminal density profiles of state-of-the-art stellar evolution calculations of the progenitor massive stars. This condition captures the vast majority of the behavior of the one hundred 2D state-of-the-art models we performed to gauge its usefulness. The goal is to predict, without resort to detailed simulation, the explodability of a given massive star. We find that the simple maximum fractional ram pressure jump discriminant we define works well ~90% of the time and we speculate on the origin of the few false positives and false negatives we witness. The maximum ram pressure jump generally occurs at the time of accretion of the silicon/oxygen interface, but not always. Our results depend upon the fidelity with which the current implementation of our code Fornax adheres to Nature and issues concerning the neutrino-matter interaction, the nuclear equation of state, the possible effects of neutrino oscillations, grid resolution, the possible role of rotation and magnetic fields, and the accuracy of the numerical algorithms employed remain to be resolved. Nevertheless, the explodability condition we obtain is simple to implement, shows promise that it might be further generalized while still employing data from only the unstable Chandrasekhar progenitors, and is a more credible and robust simple explosion predictor than can currently be found in the literature.