Bayesian inference on compact binary inspiral gravitational radiation signals in interferometric data

Details Bayesian inference on compact binary inspiral gravitational radiation signals in interferometric data Bayesian inference on compact binary inspiral gravitational radiation signals in interferometric data

2006-02-17

arxiv.org/abs/gr-qc/0602067v2

Class.Quant.Grav.23:4895-4906,2006

Astronomy and Astrophysics

Astrophysics

General Relativity and Quantum Cosmology

submitted to Classical and Quantum Gravity. 14 pages, 5 figures

Scientific paper

10.1088/0264-9381/23/15/009

Presented is a description of a Markov chain Monte Carlo (MCMC) parameter estimation routine for use with interferometric gravitational radiational data in searches for binary neutron star inspiral signals. Five parameters associated with the inspiral can be estimated, and summary statistics are produced. Advanced MCMC methods were implemented, including importance resampling and prior distributions based on detection probability, in order to increase the efficiency of the code. An example is presented from an application using realistic, albeit fictitious, data.

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