I am a Professor of Astrophysics at the Dunlap Institute in the Department of Astronomy and Astrophysics at the University of Toronto in Canada.
Tel: +1 (416) 978-4971
Email: hlozek at dunlap dot
utoronto do ca
Type Ia supernovae come from massive stellar explosions in binary systems, and act as standard candles, allowing us to measure relative distances in the universe.
Next generation Type Ia supernova (SN Ia) surveys will yield vast numbers of photometric SN candidates, without the possibility of spectroscopic follow-up. Bayesian Estimation Applied to Multiple Species (BEAMS) is a robust statistical method developed to use all available data in statistical SN analysis, when one population is contaminated by interlopers.
The figure above from Hlozek et al. 2012 shows how applying BEAMS to the full photometric sample of the Sloan Digital Sky Survey (SDSS, right panel) Supernova survey (including the low-probability, or 'redder' points) decreases the size of the error contours (compare the pink filled contours in the left panel with the blue contours, which are from spectroscopic subsets of the data).