Bayesian group finder applied to the 2MRS data

At fixed temperature, the SA algorithm is a Monte Carlo sampler of the probability density. Hence, the method provides "for free" additional information such as the probabilities that a point or two points in the observation domain belong to the cluster pattern, respectively. These supplementary tools allow the construction of tests and techniques to validate and to refine the detection result.

To test the feasibility of the proposed methodology, we applied it to the well-studied 2MASS Redshift Survey (2MRS) data set. Compared to previously published Friends-of-Friends (FoF) group finders, the proposed Bayesian group finder gives overall similar results. However, for specific applications, like the reconstruction of the local Universe, the details of the grouping algorithms are important.