New version v1.5.1 now available (April 2011). Click here to see the new features. Some changes to the MultiNest sampler to make it more robust on different architectures. There might be some sampling issues with the previous version (v1.5) on some architectures, so we recommend upgrading to v1.5.1 and checking the accuracy of the samples obtained with v1.5. Online plotting routine now available here.

SuperBayeS is a package for fast and efficient sampling of supersymmetric theories. It uses Bayesian techniques to explore multidimensional SUSY parameter spaces and to compare SUSY predictions with observable quantities, including sparticle masses, collider observables, dark matter abundance, direct detection cross sections, indirect detection quantities etc. Scanning can be performed using Markov Chain Monte Carlo (MCMC) technology or even more efficiently by employing a new scanning technique called, MultiNest. which implements the nested sampling algorithm. Using MultiNest, a full 8-dimensional scan of the CMSSM takes about 12 hours on 10 2.4GHz CPU's. There is also an option for old-style fixed-grid scanning. More info about the package can be found throughout this site. If you discover any bug or if you have any questions, please login on the SuperBayeS discussion forum.

The package combines SoftSusy, DarkSusy, FeynHiggs, Bdecay, MultiNest and MicrOMEGAs. Some of the routines and the plotting tools are based on CosmoMC.

SuperBayeS now comes with SuperEGO, a MATLAB graphical user interface tool for interactive plotting of the results. SuperEGO has been developed by Rachid Lemrani and is based on CosmoloGUI by Sarah Bridle.

Users are kindly requested to add the following statement (or something to the same effect) to their acknowledgements in any publication using SuperBayeS: The author(s) acknowledge the use of the SuperBayeS package, which includes the independently developed codes SoftSusy, DarkSUSY, MicrOMEGAs, FeynHiggs, Bdecay and MultiNest and which employs some of the CosmoMC package routines.

If you use the package, please acknowledge the following references. Also, you might want to read the original papers ( hep-ph/0602028 , astro-ph/0609126, hep-ph/0611173, arXiv:0704.3704, arXiv:0809.3437, arXiv:0705.2012, arXiv:0809.3792, arXiv:0906.0366 and arXiv:1101.3296 ) where the method is described in some detail.