4.7 Article

Constructing gravitational waves from generic spin-precessing compact binary inspirals

期刊

PHYSICAL REVIEW D
卷 95, 期 10, 页码 -

出版社

AMER PHYSICAL SOC
DOI: 10.1103/PhysRevD.95.104004

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资金

  1. Onassis Foundation
  2. NSF CAREER [PHY-1250636, PHY-1055103]
  3. NSF [PHY-1306702]
  4. NASA [NNX16AB98G]
  5. FCT under the IF2014 Programme [IF/00797/2014/CP1214/CT0012]
  6. H-MSCA-RISE Grant [StronGrHEP-690904]
  7. Centre National d'Etudes Spatiales
  8. Division Of Physics
  9. Direct For Mathematical & Physical Scien [1250636, 1607343] Funding Source: National Science Foundation

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The coalescence of compact objects is one of the most promising sources, as well as the source of the first detections, of gravitational waves for ground-based interferometric detectors, such as advanced LIGO and Virgo. Generically, compact objects in binaries are expected to be spinning with spin angular momenta misaligned with the orbital angular momentum, causing the orbital plane to precess. This precession adds rich structure to the gravitational waves, introducing such complexity that an analytic closed-form description has been unavailable until now. We here construct the first closed-form frequency-domain gravitational waveforms that are valid for generic spin-precessing quasicircular compact binary inspirals. We first construct time-domain gravitational waves by solving the post-Newtonian precession equations of motion with radiation reaction through multiple scale analysis. We then Fourier transform these time-domain waveforms with the method of shifted uniform asymptotics to obtain closed-form expressions for frequency-domain waveforms. We study the accuracy of these analytic, frequency-domain waveforms relative to waveforms obtained by numerically evolving the post-Newtonian equations of motion and find that they are suitable for unbiased parameter estimation for 99.2%(94.6%) of the binary configurations we studied at a signal-to-noise ratio of 10(25). These new frequency-domain waveforms could be used for detection and parameter estimation studies due to their accuracy and low computational cost.

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