Extracting galactic binary signals from the first round of Mock LISA Data Challenges

Details Extracting galactic binary signals from the first round of Mock LISA Data Challenges Extracting galactic binary signals from the first round of Mock LISA Data Challenges

2007-04-23

arxiv.org/abs/0704.2917v1

Class.Quant.Grav.24:S575-S586,2007

Astronomy and Astrophysics

Astrophysics

General Relativity and Quantum Cosmology

13 pages, 4 figures, submitted to Proceedings of GWDAW-11 (Berlin, Dec. '06)

Scientific paper

10.1088/0264-9381/24/19/S20

We report on the performance of an end-to-end Bayesian analysis pipeline for detecting and characterizing galactic binary signals in simulated LISA data. Our principal analysis tool is the Blocked-Annealed Metropolis Hasting (BAM) algorithm, which has been optimized to search for tens of thousands of overlapping signals across the LISA band. The BAM algorithm employs Bayesian model selection to determine the number of resolvable sources, and provides posterior distribution functions for all the model parameters. The BAM algorithm performed almost flawlessly on all the Round 1 Mock LISA Data Challenge data sets, including those with many highly overlapping sources. The only misses were later traced to a coding error that affected high frequency sources. In addition to the BAM algorithm we also successfully tested a Genetic Algorithm (GA), but only on data sets with isolated signals as the GA has yet to be optimized to handle large numbers of overlapping signals.

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