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Resolving multiple supermassive black hole binaries with pulsar timing arrays II: genetic algorithm implementation

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Petiteau,  Antoine
Astrophysical Relativity, AEI-Golm, MPI for Gravitational Physics, Max Planck Society;

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Babak,  Stanislav
Astrophysical Relativity, AEI-Golm, MPI for Gravitational Physics, Max Planck Society;

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Sesana,  Alberto
Astrophysical Relativity, AEI-Golm, MPI for Gravitational Physics, Max Planck Society;

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1210.2396.pdf
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PRD87_064036.pdf
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引用

Petiteau, A., Babak, S., Sesana, A., & de Araujo, M. (2013). Resolving multiple supermassive black hole binaries with pulsar timing arrays II: genetic algorithm implementation. Physical Review D, 87:. doi:10.1103/PhysRevD.87.064036.


引用: https://hdl.handle.net/11858/00-001M-0000-0015-1927-E
要旨
Pulsar timing arrays (PTAs) might detect gravitational waves (GWs) from massive black hole (MBH) binaries within this decade. The signal is expected to be an incoherent superposition of several nearly-monochromatic waves of different strength. The brightest sources might be individually resolved, and the overall deconvolved, at least partially, in its individual components. In this paper we extend the maximum-likelihood based method developed in Babak & Sesana 2012, to search for individual MBH binaries in PTA data. We model the signal as a collection of circular monochromatic binaries, each characterized by three free parameters: two angles defining the sky location, and the frequency. We marginalize over all other source parameters and we apply an efficient multi-search genetic algorithm to maximize the likelihood function and look for sources in synthetic datasets. On datasets characterized by white Gaussian noise plus few injected sources with signal-to-noise ratio (SNR) in the range 10-60, our search algorithm performs well, recovering all the injections with no false positives. Individual source SNRs are estimated within few % of the injected values, sky locations are recovered within few degrees, and frequencies are determined with sub-Fourier bin precision.