Impact of neutrino pair-production rates in Core-Collapse Supernovae

TL;DR

This study investigates how different models of neutrino pair-production affect the evolution, neutrino signals, and explosion dynamics in core-collapse supernova simulations, emphasizing the importance of microphysics accuracy.

Contribution

It compares simplified and complete treatments of neutrino pair-production processes, highlighting their impact on supernova simulation outcomes and suggesting the use of state-of-the-art microphysics for precision.

Findings

Simplified neutrino pair-production models impact neutrino signals by about 10%.

Choice of nucleon-nucleon bremsstrahlung affects neutrino signal quantitatively.

Simplified models produce qualitatively similar supernova evolution with less computational cost.

Abstract

In this paper, we present a careful study on the impact of neutrino pair-production on core-collapse supernovae via spherically-symmetric, general-relativistic simulations of two different massive star progenitors with energy-dependent neutrino transport. We explore the impact and consequences of both the underlying microphysics and the implementation in the radiation transport algorithms on the supernova evolution, neutrino signal properties, and the explosion dynamics. We consider the two dominant neutrino pair-production processes found in supernovae, electron-positron annihilation as well as nucleon-nucleon bremsstrahlung in combination with both a simplified and a complete treatment of the processes in the radiation transport algorithms. We find that the use of the simplified prescription quantitatively impacts the neutrino signal at the 10\% level and potentially the supernova dynamics, as we show for the case of a 9.6M$_\odot$ progenitor. We also show that the choice of nucleon-nucleon bremsstrahlung interaction can also have a quantitative impact on the neutrino signal. A self-consistent treatment with state-of-the-art microphysics is suggested for precision simulations of core collapse, however the simplified treatment explored here is both computationally less demanding and results in a qualitatively similar evolution.