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  Systematic biases in parameter estimation of binary black-hole mergers

Littenberg, T. B., Baker, J. G., Buonanno, A., & Kelly, B. J. (2013). Systematic biases in parameter estimation of binary black-hole mergers. Physical Review D, 87(10): 104003. doi:10.1103/PhysRevD.87.104003.

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 Urheber:
Littenberg, Tyson B., Autor
Baker, John G., Autor
Buonanno, A.1, 2, Autor           
Kelly, Bernard J., Autor
Affiliations:
1Astrophysical and Cosmological Relativity, AEI-Golm, MPI for Gravitational Physics, Max Planck Society, ou_1933290              
2Maryland Center for Fundamental Physics & Joint Space-Science Center, Department of Physics, University of Maryland , ou_persistent22              

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Schlagwörter: General Relativity and Quantum Cosmology, gr-qc
 Zusammenfassung: Parameter estimation of binary-black-hole merger events in gravitational-wave data relies on matched-filtering techniques, which, in turn, depend on accurate model waveforms. Here we characterize the systematic biases introduced in measuring astrophysical parameters of binary black holes by applying the currently most accurate effective-one-body templates to simulated data containing non-spinning numerical-relativity waveforms. For advanced ground-based detectors, we find that the systematic biases are well within the statistical error for realistic signal-to-noise ratio (SNR). These biases grow to be comparable to the statistical errors at high ground-based-instrument SNRs (SNR=50), but never dominate the error budget. At the much larger signal-to-noise ratios expected for space-based detectors, these biases will become large compared to the statistical errors, but for astrophysical black hole mass estimates the absolute biases (of at most a few percent) are still fairly small.

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 Datum: 2012-10-022013
 Publikationsstatus: Erschienen
 Seiten: 16 Pages, 7 figures
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Titel: Physical Review D
  Andere : Phys. Rev. D.
Genre der Quelle: Zeitschrift
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Ort, Verlag, Ausgabe: Lancaster, Pa. : American Physical Society
Seiten: - Band / Heft: 87 (10) Artikelnummer: 104003 Start- / Endseite: - Identifikator: ISSN: 0556-2821
CoNE: https://pure.mpg.de/cone/journals/resource/111088197762258