zeus: A Python implementation of Ensemble Slice Sampling for efficient Bayesian parameter inference

Understand

We introduce zeus, a well-tested Python implementation of the Ensemble Slice Sampling (ESS) method for Bayesian parameter inference.

• ESS is a novel Markov chain Monte Carlo (MCMC) algorithm specifically designed to tackle the computational challenges posed by modern astronomical and cosmological analyses.
• In particular, the method requires only minimal hand--tuning of 1-2 hyper-parameters that are often trivial to set; its performance is insensitive to linear correlations and it can scale up to 1000s of CPUs without any extra effort.
• Furthermore, its locally adaptive nature allows to sample efficiently even when strong non-linear correlations are present.