BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//CERN//INDICO//EN
BEGIN:VEVENT
SUMMARY:Bayesian and Brisk: Scalable AGN Lightcurve Simulation and Fitting
  for Supernova Cosmology and Population Studies
DTSTART;VALUE=DATE-TIME:20261028T182200Z
DTEND;VALUE=DATE-TIME:20261028T182300Z
DTSTAMP;VALUE=DATE-TIME:20261026T232823Z
UID:indico-contribution-3716@nyx.physics.mcgill.ca
DESCRIPTION:Speakers: Zoe Augspach (University of Toronto)\nActive Galacti
 c Nuclei (AGNs) are dense\, bright regions at the centre of galaxies thoug
 ht to be caused by matter accreting into a supermassive black hole. Millio
 ns of AGNs have been observed\, and population-level studies are needed to
  learn about AGN physics. \n\nOn the other hand\, AGNs can be contaminants
  in cosmology. Type 1a supernovae are frequently used as “standard candl
 es” to infer cosmological parameters by estimating both their redshift a
 nd distance modulus to trace cosmic expansion. The Legacy Survey of Space 
 and Time (LSST) will observe millions of supernovae photometrically. Since
  few Type 1as will be spectroscopically confirmed\, other transients can b
 e confused for Type 1as due to low cadence and different sources of uncert
 ainty\, such as instrument noise and model uncertainty. All sources of unc
 ertainty\, including the uncertainty in the label of the source\, must be 
 propagated throughout the model in a fully Bayesian manner to acquire cred
 ible intervals for the inferred cosmological parameters. This is what the 
 package *Cosmographi* aims to do\, while remaining scalable by using JAX. 
 \n\nThis work will present the forward model and fitting modules for AGNs 
 within the *Cosmographi* framework. The user will be able to produce simul
 ated lightcurves orders of magnitude faster compared to pre-existing metho
 ds. Moreover\, it allows for fully Bayesian lightcurve fitting\, and infer
 ence of cosmological parameters from a population with different types of 
 transients. \n\nIn conclusion\, we present advances towards a fully Bayesi
 an estimation of cosmological parameters from millions of supernovae\, and
  population-level studies of AGNs.\n\nhttps://nyx.physics.mcgill.ca/event/
 587/contributions/3716/
LOCATION:Online 
URL:https://nyx.physics.mcgill.ca/event/587/contributions/3716/
END:VEVENT
END:VCALENDAR