Exploration of Aspherical Ejecta Properties in Type Ia Supernova: Progenitor Dependence and Applications to Progenitor Classification

Abstract

Several explosions of thermonuclear supernovae (SNe Ia) have been found to exhibit deviations from spherical symmetry upon closer inspection. Examples are the gamma-ray lines from SN 2014J as measured by INTEGRAL/SPI, and morphology information from radioactive isotopes in older remnants such as Tycho. A systematic study on the effects of parameters such as ignition geometry and burning morphology in SNe Ia is still missing. We use a 2D hydrodynamics code with post-processing nucleosynthesis and simulate the double detonations in a sub-Chandrasekhar mass carbon-oxygen white dwarf starting from the nuclear runaway in the accumulated He envelope towards disruption of the white dwarf. We explore potential variety through four triggering scenarios that sample main asymmetry drivers. We further investigate their global effects on the aspherical structure of the ejecta based on individual elements. We apply the results to the well observed SN 2014J and other recently observed SN remnants in order to illustrate how these new observational data together with other observed quantities help to constrain the explosion and the progenitors of SNe Ia.

Evidence for strong progenitor age dependence of type Ia supernova luminosity standardization process

“…It appears that an increasing progenitor mass (with younger age) produces a brighter SN with a broader light curve and bluer color, following the green arrows in schematic diagrams in Figure 5. Theoretical models for type Ia SN are still incomplete, but a leading theory suggests that the WLR is mostly due to the asymmetry of ignition and detonation (Kasen et al 2009), while other studies show that the SN peak luminosity increases with Ni mass formed in the explosion, which in turn increases with progenitor mass (Woosley et al 2007;Leung et al 2020). Therefore, taken together, the trend we can infer from Figure 5 is qualitatively consistent with model predictions, while more detailed modeling is required for the quantitative comparison.…”