Light and Color Curve Properties of Type Ia Supernovae: Theory Versus Observations

Abstract

We study optical light curve(LC) relations of type Ia supernovae(SNe Ia) for their use in cosmology using high-quality photometry published by the Carnegie-Supernovae-Project(CSP-I). We revisit the classical luminosity-decline-rate (∆m 15 ) relation and the Lira-relation, as well as investigate the time evolution of the (B −V ) color and B(B −V ), which serves as the basis of the color-stretch relation and Color-MAGnitude-Intercept-Calibrations(CMAGIC). Our analysis is based on explosion and radiation transport simulations for spherically-symmetric delayed-detonation models(DDT) producing normalbright and subluminous SNe Ia. Empirical LC-relations can be understood as having the same physical underpinnings: i.e. the opacities, ionization balances in the photosphere, and radioactive energy deposition changing with time from below to above the photosphere. Some 3−4 weeks past maximum, the photosphere recedes to 56 Ni-rich layers of similar density structure, leading to a similar color evolution. An important secondary parameter is the central density ρ c of the WD because at higher densities more electron capture elements are produced at the expense of 56Ni production. This results in a ∆m 15 spread of 0.1 mag for normal-bright and 0.7 mag in sub-luminous SNe Ia and ≈ 0.2 mag in the Lira-relation. We show why color-magnitude diagrams emphasize the transition between physical regimes, and enables the construction of templates which depend mostly on ∆m 15 with little dispersion in both the CSP-I sample and our DDT-models. This allows to separate intrinsic SN Ia variations from the interstellar reddening characterized by E(B −V ) and R B . Invoking different scenarios causes a wide spread in empirical relations which may suggest one dominant scenario.

Two transitional type Ia supernovae located in the Fornax cluster member NGC 1404: SN 2007on and SN 2011iv

“…As shown in Hoeflich et al (2017), the offset is relatively stable over the period of the Lira relation for models of different brightness. We note that a similar result was also found from the detailed analysis of the low-luminosity SN 1986G (Ashall et al 2016b).…”

“…While ρ tr is the primary driver of the luminosity vs. decline-rate relation, ρ c plays an important role for the fasterdeclining SNe Ia which produce smaller amounts of radioactive 56 Ni as compared to normal-luminosity SNe Ia. In SNe with the same ∆m 15 (B) (so-called "twins"), this secondary parameter can lead to changes in the peak brightness of 0.05 mag for normalbrightness SNe Ia, and by up to 0.7 mag in the case of twin subluminous SNe Ia (Hoeflich et al 2017). Höflich et al (2010) studied the variation in brightness between the peak and the tail (roughly the brightness at day +40) caused by variations in progenitor mass, metallicity, accretion rate,Ṁ, and central density.…”

“…Höflich et al (2010) studied the variation in brightness between the peak and the tail (roughly the brightness at day +40) caused by variations in progenitor mass, metallicity, accretion rate,Ṁ, and central density. The effects of variations in ρ c are further elucidated in Figure 7 of Hoeflich et al (2017), which shows the variation of heating from gamma-ray deposition as a function of central concentration of radioactive nickel. This more central heating in lower-ρ c SNe leads to a hotter central region and therefore bluer colours, with a variation in B − V of up to 0.2 mag.…”

“…As a baseline we use models originating from a 5 M ⊙ main sequence star with solar metallicity (Hoeflich et al 2002). The best-fit model parameters are determined from the interpolations of an extend grid of DD models with ρ c = 0.5...6 × 10 using the ∆m 15 − CMAGIC optimization for determining the model parameters (Hoeflich et al 2017).…”

Extracting high-level information from gamma-ray burst supernova spectra

“…In time domain astrophysics both types of codes have been throughly used to model many different transient sources including: core collapse supernovae (e.g., Hoflich 1991; Baron et al 1995;Fisher 2000;Mazzali et al 2000;Thomas et al 2011;Jerkstrand et al 2012), thermonuclear supernovae (e.g., Kasen et al 2006;Kromer & Sim 2009;Kerzendorf & Sim 2014;Ashall et al 2016;Hoeflich et al 2017;Goldstein & Kasen 2018;Ashall et al 2018), and more recently kilonova (e.g., Tanaka & Hotokezaka 2013;Smartt et al 2017;Bulla 2019). However, previous work has concentrated on the results obtained from these models, and often E-mail:chris.ashall24@gmail.com neglected to explain the exact modeling method, fitting procedure or associated errors.…”