Low Mass SN Ia and the Late Light Curve

Abstract

The late bolometric light curves of type Ia supernovae, when measured accurately over several years, show an exponential decay with a 56d half-life over a drop in luminosity of 8 magnitudes (10 half-lives). The late-time light curve is thought to be governed by the decay of Co56, whose 77d half-life must then be modified to account for the observed decay time. Two mechanisms, both relying upon the positron fraction of the Co56 decay, have been proposed to explain this modification. One explanation requires a large amount of emission at infra-red wavelengths where it would not be detected(Axelrod, 1980a, Axelrod, 1980b). The other explanation has proposed a progressive transparency or leakage of the high energy positrons (Colgate, Petschek and Kriese, 1980). For the positrons to leak out of the expanding nebula at the required rate necessary to produce the modified 56d exponential, the mass of the ejecta from a one foe (1051 erg in kinetic energy) explosion must be small, M ejec = 0.4M ⊙ with M ejec ∝ KE 0.5. Thus, in this leakage explanation, any reasonable estimate of the total energy of the explosion requires that the ejected mass be very much less than the Chandrasekhar mass of 1.4M ⊙. This is very difficult to explain with the “canonical” Chandrasekhar-mass thermonuclear explosion that disintegrates the original white dwarf star. This result leads us to pursue alternate mechanisms of type Ia supernovae. These mechanisms include sub-Chandrasekhar thermonuclear explosions and the accretion induced collapse of Chandrasekhar mass white dwarfs. We will summarize the advantages and disadvantages of both mechanisms with considerable detail spent on our new accretion induced collapse simulations. These mechanisms lead to lower Ni56 production and hence result in type la supernovae with luminosities decreased down to ~ 50% that predicted by the “standard” model.KeywordsNeutron StarLight CurveDeposition FractionPositron FractionPeak LuminosityThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.