Aula Conversi (Dipartimento di Fisica - Ed. G. Marconi)
Aula Conversi
Dipartimento di Fisica - Ed. G. Marconi
Description
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 produce unbiased estimates of the parameters. BEAMS is a gener! al technique which should be applied in any situation where contamination from other types of objects is possible. In this colloquium, I will explain how BEAMS works and how it is applied to supernova cosmology. I will also briefly discuss my current work on extending BEAMS to deal with correlated data.