Abstract
An algorithm for identifying rings in Ring Imaging Cherenkov (RICH) detectors is
described. The algorithm is necessarily Bayesian and makes use of a Metropolis-
Hastings Markov chain Monte Carlo sampler to locate the rings. In particular, the
sampler employs a novel proposal function whose form is responsible for significant
speed improvements over similar methods. The method is optimised for finding
multiple overlapping rings in detectors which can be modelled well by the LHbC
RICH toy model described herein.