Bayesclumpy: Bayesian Inference with Clumpy Dusty Torus Models
Our aim is to present a fast and general Bayesian inference framework based on the synergy between machine learning techniques and standard sampling methods and apply it to infer the physical properties of clumpy dusty torus using infrared photometric high spatial resolution observations of active galactic nuclei. We make use of the Metropolis
Asensio Ramos, A. et al.
Fecha de publicación:
5
2009