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SUMMARY:High-Dimension Bayesian Model Comparison in Cosmology - Toby Lovic
 k / IoA
DTSTART:20251008T121500Z
DTEND:20251008T124000Z
UID:TALK237892@talks.cam.ac.uk
CONTACT:Xander Byrne
DESCRIPTION:Our recent work (2509.13307) demonstrated the performance of G
 PU-accelerated nested sampling for efficient high-dimensional Bayesian inf
 erence in cosmology. Using JAX-based emulators and likelihoods we can leve
 rage the parallel computing of GPUs to achieve orders of magnitude speed-u
 ps against CPU-based analyses\, and bring robust evidence calculations up 
 to GPU-speed. This puts nested sampling back on equal footing with Markov 
 Chain Monte Carlo (MCMC) methods\, which use auto-diff gradients to achiev
 e their speed-ups. In particular a Euclid-like mock Cosmic Shear likelihoo
 d has been considered\, an analysis which previously took 8 months on a CP
 U instance\, and we bring the time to constrain both ΛCDM and w0wa down t
 o only 2 days on a single GPU. This talk explores a few options for pushin
 g our methodology even further\, in preparation for joint analyses of next
  generation of cosmlogical surveys.
LOCATION:Hoyle Lecture theatre + Zoom 
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