Speaker
Sven Günther
(RWTH Aachen University - Institute for Theoretical Particle Physics and Cosmology)
Description
Bayesian parameter inference is one of the key elements for model selection in cosmological research. However, the inference tools require a large number of calls to simulation codes which can lead to high and sometimes even infeasible computational costs. In this work we combine fast and differentiable emulators with active sampling to accelerate MCMC analyses of CMB physics by 1-2 magnitudes and save 2-3 magnitudes of simulation calls. In particular, this novel approach emphasizes the uncertainty-awareness of the emulator, which allows to state the emulation accuracy and ensures reliable performance where needed.
Author
Sven Günther
(RWTH Aachen University - Institute for Theoretical Particle Physics and Cosmology)
