Type Ia supernovae (SNe Ia) play a number of key roles in astrophysics. These include synthesising heavy elements such as iron, injecting kinetic energy in galaxy evolution and acting as cosmological distance indicators. Despite this, however, the way in which SNe Ia occur is still poorly understood and there is currently no definitive explosion scenario that explains SNe Ia. Additionally, thanks to data from modern transient surveys, it has become clear that while “normal” SNe Ia make up a relatively homogenous sequence of objects, there exist a number of “peculiar” sub-classes within the SNe Ia population. Among the largest of these sub-groups is the set of Type Iax supernovae (SNe Iax), which were estimated by Foley et al. (2013) to make up 31-11+17% of the SNe Ia population. SNe Iax are a diverse class of objects that are sub-luminous and span a much wider range in brightness compared to normal SNe Ia.
Understanding which explosion mechanism(s) produce different SNe Ia is a key research question. The Chandrasekhar-mass, pure-deflagration model has long been suggested as a possible explosion mechanism to explain SNe Ia. In this scenario, a carbon-oxygen white dwarf accretes material from a companion star until it approaches the Chandrasekhar mass limit. Nuclear reactions are then ignited in the white dwarf’s core, which leads to a thermonuclear runaway. The resulting explosive energy release will gravitationally unbind either part or all of the white dwarf. When it is assumed that the propagation of the nuclear burning front is a sub-sonic deflagration, this model struggles to account for the high luminosities of “normal” SNe Ia. However, studies have shown that pure-deflagration models with variations to their initial conditions can explain a wide variety of the observed properties of SNe Iax.
Our DiRAC project involves using computer simulations of radiative transfer to predict the spectrum of light that would be emitted by theoretical models of supernovae. We use the comparison between these simulations and observed supernovae to better understand the underlying explosion models and gain insight into which explosion models are favoured and disfavoured by the data for each specific sub-class of supernovae observed. The work we highlight here specifically focusses on the Chandrasekhar-mass, pure-deflagration scenario as a possible explosion scenario to explain the SNe Iax class.
Previous deflagration models of Fink et al. (2014) varied the number of ignition sparks used to initiate the deflagration as a way of varying the strength of the explosion and found that a variety of SNe Iax properties could be explained in this way. However, the previous models did not account for the full range of observed luminosities and, moreover, the multi-spark ignition approach has been shown by Nonaka et al. (2012) and Zingale et al. (2011) to be less probable than single-spark ignition. Therefore, in collaboration with our colleagues at the Heidelberg Institute for Theoretical Studies, we have carried out a new set of deflagration simulations to systematically explore the degree of diversity that can be accounted for with single-spark ignition models by varying the ignition position, central density, and composition. Sample results are shown in the accompanying figure. Our results indicate the deflagration scenario can cover a significant region of the parameter space occupied by observed SNe Iax. In particular, the models may be almost a magnitude fainter than the models in the Fink et al. (2014) sequence, and thus give luminosities extending down to the faintest SNe Iax. This work (to be published in a paper led by our collaborators) has therefore confirmed the full observed diversity in brightness of the SNe Iax class can be explained by pure deflagrations of Chandrasekhar-mass, carbon-oxygen white dwarfs. However, systematic differences between models and data remain and require further investigation. We are therefore currently working on refining simulations with more advanced microphysics (Shingles et al. 2020) to better understand these differences. We intend to publish this follow up work later this year.
This work also used the Cambridge Service for Data Driven Discovery (CSD3), part of which is operated by the University of Cambridge Research Computing on behalf of the STFC DiRAC HPC Facility (www.dirac.ac.uk).
- Fink et al., 2014, MNRAS, 438, 1762
- Foley et al., 2013, ApJ, 767, 57
- Nonaka et al., 2012, ApJ, 745, 73
- Shingles et al., 2020, MNRAS, 492, 2029
- Zingale et al., 2009, ApJ, 704, 196