Comparison of Spectral Classification and Sperctral-Series Classification of Supernovae

  Samantha Goldwasser  ,  Ofek Bengiat  
Weizmann Institute of Science

Our project is the comparison of two different classification schemes for supernovae. The first classification tool is the new python SuperFit (a chi squared minimizer), which classifies supernovae at a specific phase. The second tool is a random-forest inspired approach based on the supernovae's spectral series through time.
In order to perform the comparison we use a data base consisting of 75 supernovae whose spectral series were interpolated and calibrated using PyCoCo.
We expect for this comparison to serve as a test for both methods on the way to a time-domain-aware classification scheme for supernovae.