Talk detail

Participant	Knights, Michelle
Institution	African Institute of Mathematical Sciences/ University of Cape Town - 6 Melrose Road, Muizenberg - Cape Town - Western Cape - South Africa

Session	OC1	Accepted	Yes	Order	7	Time	17:10 - 17:30	20'
Talk	Oral abstract	Title	Towards the future of Supernova Cosmology
Co-authors	Bruce Bassett, Martin Kunz
Abstract	Future surveys such as the Dark Energy Survey and the Large Synoptic Survey Telescope will produce an unprecedented amount of photometric supernova data, not all of which can be followed up spectroscopically. Light curve fitting techniques can provide a probability that an object is a type 1a supernova, but contamination from other types of supernovae can lead to biases to the estimation of cosmological parameters. BEAMS (Bayesian Estimator Applied to Multiple Species) is a fully Bayesian analysis technique designed to take contamination into account and produced unbiased estimates of the parameters. However, the current form of BEAMS relies on the assumption that the supernova data are uncorrelated, which will not be true for the large amounts of data from future surveys. We investigate two techniques to extend BEAMS to deal with correlations.