arianna 1 is a Python implementation of the Metropolis–Coupled Slice Sampling method that generates posterior samples from high-dimensional and strongly multimodal distributions. Apart from Bayesian parameter inference, arianna also provides unbiased and low-variance estimates of the model evidence (aka marginal likelihood) at no additional cost. The sampler is modular and does not require any hand-tuning from the user. Its parallel and black-box nature renders it ideal for computationally expensive models with high number of parameters often met in the physical sciences.


Named after Dr. Arianna W. Rosenbluth, one of the main developers of the Metropolis algorithm and the first person in history to ever code a Markov Chain Monte Carlo algorithm.


Please cite the following if you find this code useful in your research. The BibTeX entry for the paper is:

    title={arianna: A Metropolis--Coupled Slice Sampler for Bayesian Inference and Model Selection},
    author={Minas Karamanis and Florian Beutler},
    note={in prep}

Authors & License

Copyright 2021 Minas Karamanis and contributors.

arianna is free software made available under the GPL-3.0 License.


0.0.1 (14/03/21)

  • First version