Exploring phase space with nested sampling

We present the first application of a Nested Sampling algorithm to explore high-dimensional phase space particle collision events. describe adaptation algorithm, designed perform Bayesian inference computations, integration partonic scattering cross sections and generation individual events distributed according corresponding squared matrix element. As concrete example we consider gluon processes into 3-, 4- 5-gluon final states compare performance with established sampling techniques. Starting from flat prior distribution outperforms Vegas achieves results comparable dedicated multi-channel importance sampler. outline possible approaches combine non-flat distributions further reduce variance integral estimates increase unweighting efficiencies.