The fifth Science run of LIGO (S5) has been concluded recently. The data collected over two years of the run calls for a thorough analysis of the glitches seen in the gravitational wave channels, as well as in the auxiliary and environmental channels. The study presents two new techniques for cluster analysis of gravitational wave burst triggers. Traditional approaches to clustering treats the problem as an optimization problem in an “open” search space of clustering models. However, this can lead to problems with producing models that over-fit or under-fit the data as the search is stuck on local minima. The new algorithms tackle local minima by putting constraints in the search process. S-MEANS looks at similarity statistics of burst triggers and builds up clusters that have the advantage of avoiding local minima. Constrained Validation clustering tackles the problem by constraining the search in the space of clustering models that are “non-splittable” models in which centroids of the left and right child of a cluster (after splitting) are nearest to each other; the region of models that either over-fit or under-fit data (i.e. “splittable” models) can therefore be effectively avoided when assumptions about data are satisfied. These methods are demonstrated by using simulated data. The results on simulated data are promising and the methods are expected to be useful for LIGO S5 data analysis.
Tang, Lappoon R.; Lei, Hansheng; Mukherjee, Soma; and Mohanty, Soumya, "Cluster Analysis of Simulated GravitationalWave Triggers Using S-MEANS and Constrained Validation Clustering" (2008). Computer Science Faculty Publications and Presentations. 14.
Classical and Quantum Gravity