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Abstract: We describe an application of the MultiNest algorithm to gravitational wavedata analysis. MultiNest is a multimodal nested sampling algorithm designed toefficiently evaluate the Bayesian evidence and return posterior probabilitydensities for likelihood surfaces containing multiple secondary modes. Thealgorithm employs a set of live points which are updated by partitioning theset into multiple overlapping ellipsoids and sampling uniformly from withinthem. This set of live points climbs up the likelihood surface through nestediso-likelihood contours and the evidence and posterior distributions can berecovered from the point set evolution. The algorithm is model-independent inthe sense that the specific problem being tackled enters only through thelikelihood computation, and does not change how the live point set is updated.In this paper, we consider the use of the algorithm for gravitational wave dataanalysis by searching a simulated LISA data set containing two non-spinningsupermassive black hole binary signals. The algorithm is able to rapidlyidentify all the modes of the solution and recover the true parameters of thesources to high precision.



Autor: Farhan Feroz, Jonathan R. Gair, Michael P. Hobson, Edward K. Porter

Fuente: https://arxiv.org/







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