English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Journal Article

Probabilistic reconstruction of type Ia supernova SN 2002bo

MPS-Authors
/persons/resource/persons4732

Pakmor,  Rüdiger
Stellar Astrophysics, MPI for Astrophysics, Max Planck Society;

External Resource
No external resources are shared
Fulltext (restricted access)
There are currently no full texts shared for your IP range.
Fulltext (public)
There are no public fulltexts stored in PuRe
Supplementary Material (public)
There is no public supplementary material available
Citation

O’Brien, J. T., Kerzendorf, W. E., Fullard, A., Williamson, M., Pakmor, R., Buchner, J., et al. (2021). Probabilistic reconstruction of type Ia supernova SN 2002bo. The Astrophysical Journal Letters, 916(2): L14. doi:10.3847/2041-8213/ac1173.


Cite as: https://hdl.handle.net/21.11116/0000-0009-5FC1-3
Abstract
Manual fits to spectral times series of Type Ia supernovae have provided a method of reconstructing the explosion from a parametric model but due to lack of information about model uncertainties or parameter degeneracies direct comparison between theory and observation is difficult. In order to mitigate this important problem we present a new way to probabilistically reconstruct the outer ejecta of the normal Type Ia supernova SN 2002bo. A single epoch spectrum, taken 10 days before maximum light, is fit by a 13-parameter model describing the elemental composition of the ejecta and the explosion physics (density, temperature, velocity, and explosion epoch). Model evaluation is performed through the application of a novel rapid spectral synthesis technique in which the radiative transfer code, TARDIS, is accelerated by a machine-learning framework. Analysis of the posterior distribution reveals a complex and degenerate parameter space and allows direct comparison to various hydrodynamic models. Our analysis favors detonation over deflagration scenarios and we find that our technique offers a novel way to compare simulation to observation.