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SUMMARY:Towards the Future of Supernova Cosmology - Michelle Knights (Univ
 ersity of Cape Town)
DTSTART:20130613T103000Z
DTEND:20130613T113000Z
UID:TALK44795@talks.cam.ac.uk
CONTACT:David Titterington
DESCRIPTION:Future surveys such as the Dark Energy Survey and the Large Sy
 noptic Survey Telescope will produce an unprecedented amount of photometri
 c supernova data\, not all of which can be followed up spectroscopically. 
  Light curve fitting techniques can provide a probability that an object i
 s a Type Ia supernova\, but contamination from other types of supernovae c
 an lead to biases to the estimation of cosmological parameters.  BEAMS (Ba
 yesian Estimation Applied to Multiple Species) is a fully Bayesian analysi
 s technique designed to take contamination into account and produce unbias
 ed estimates of the parameters.  BEAMS is a general technique which should
  be applied in any situation where contamination from other types of objec
 ts is possible.  In this colloquium\, I will explain how BEAMS works and h
 ow it is applied to supernova cosmology.  I will also discuss my current w
 ork on extending BEAMS to deal with correlated data and comparing BEAMS wi
 th an alternative Monte Carlo approach.\n
LOCATION:Ryle Seminar Room\, Cavendish Laboratory
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