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SUMMARY:Correcting for Malmquist Bias in Type Ia Supernova Cosmology - Ben
  Boyd
DTSTART:20240214T131500Z
DTEND:20240214T134000Z
UID:TALK212260@talks.cam.ac.uk
CONTACT:107642
DESCRIPTION:Type Ia supernovae (SNe Ia) can be standardised to provide dis
 tance estimates to put constraints on cosmological parameters. When buildi
 ng a sample for this\, astrophysical selection effects mean that we are bi
 ased towards detecting SNe Ia with certain characteristics. The most famou
 s example is Malmquist bias\, meaning surveys are more likely to detect br
 ighter SNe towards the edge of their limiting magnitudes. This disproporti
 onally bright sample at high redshifts leads to an underestimation of dist
 ances on the Hubble diagram. If we fit for cosmological parameters naively
  without accounting for this effect\, we will bias our constraints on fund
 amental parameters. In this presentation I will cover some of the existing
  methods to correct for Malmquist bias. I will then outline our own method
  that combines simulation-based inference and hierarchical Bayesian modell
 ing. Simple simulations will be used to demonstrate our method can match a
 nalytical solutions. I will conclude by discussing plans to show the gener
 alisation of our flexible method to real survey selection effects where an
 alytical solutions are intractable. 
LOCATION:The Hoyle Lecture Theatre + Zoom 
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