Pulsating reverse detonation models of Type Ia supernovae. II: Explosion

TL;DR

This paper presents 3D simulations of Pulsating Reverse Detonation models for Type Ia supernovae, demonstrating their potential to produce explosion energies and nickel masses consistent with observations.

Contribution

It introduces detailed 3D numerical simulations of PRD models, exploring their explosion mechanisms and resulting observable properties, advancing understanding of Type Ia supernovae origins.

Findings

Explosions with energies ~1.0-1.2 foes and 56Ni masses ~0.6-0.8 M_sun.

PRD models can reproduce typical supernova spectra and light curves.

Simulations support PRD as a viable explosion mechanism for Type Ia supernovae.

Abstract

Observational evidences point to a common explosion mechanism of Type Ia supernovae based on a delayed detonation of a white dwarf. However, all attempts to find a convincing ignition mechanism based on a delayed detonation in a destabilized, expanding, white dwarf have been elusive so far. One of the possibilities that has been invoked is that an inefficient deflagration leads to pulsation of a Chandrasekhar-mass white dwarf, followed by formation of an accretion shock that confines a carbon-oxygen rich core, while transforming the kinetic energy of the collapsing halo into thermal energy of the core, until an inward moving detonation is formed. This chain of events has been termed Pulsating Reverse Detonation (PRD). In this work we present three dimensional numerical simulations of PRD models from the time of detonation initiation up to homologous expansion. Different models characterized by the amount of mass burned during the deflagration phase, M_defl, give explosions spanning a range of kinetic energies, K ~ (1.0-1.2) foes, and 56Ni masses, M(56Ni) ~ 0.6-0.8 M_sun, which are compatible with what is expected for typical Type Ia supernovae. Spectra and light curves of angle-averaged spherically symmetric versions of the PRD models are discussed. Type Ia supernova spectra pose the most stringent requirements on PRD models.