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Register a new userComparing gravitational waves from nonprecessing and precessing black hole binaries in the corotating frame
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Added by
Richard O'Shaughnessy
Publication date
2013
fields
Physics
and research's language is
English
Authors
Jim Healy
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Previous analytic and numerical calculations suggest that, at each instant, the emission from a precessing black hole binary closely resembles the emission from a nonprecessing analog. In this paper we quantitatively explore the validity and limitations of that correspondence, extracting the radiation from a large collection of roughly two hundred generic black hole binary merger simulations both in the simulation frame and in a corotating frame that tracks precession. To a first approximation, the corotating-frame waveforms resemble nonprecessing analogs, based on similarity over a band-limited frequency interval defined using a fiducial detector (here, advanced LIGO) and the sources total mass $M$. By restricting attention to masses $Min 100, 1000 M_odot$, we insure our comparisons are sensitive only to our simulated late-time inspiral, merger, and ringdown signals. In this mass region, every one of our precessing simulations can be fit by some physically similar member of the texttt{IMRPhenomB} phenomenological waveform family to better than 95%; most fit significantly better. The best-fit parameters at low and high mass correspond to natural physical limits: the pre-merger orbit and post-merger perturbed black hole. Our results suggest that physically-motivated synthetic signals can be derived by viewing radiation from suitable nonprecessing binaries in a suitable nonintertial reference frame. While a good first approximation, precessing systems have degrees of freedom (i.e., the transverse spins) which a nonprecessing simulation cannot reproduce. We quantify the extent to which these missing degrees of freedom limit the utility of synthetic precessing signals for detection and parameter estimation.
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We present PhenomPNR, a frequency-domain phenomenological model of the gravitational-wave (GW) signal from binary-black-hole mergers that is tuned to numerical relativity (NR) simulations of precessing binaries. In many current waveform models, e.g., the Phenom and EOBNR families that have been used extensively to analyse LIGO-Virgo GW observations, analytic approximations are used to add precession effects to models of non-precessing (aligned-spin) binaries, and it is only the aligned-spin models that are fully tuned to NR results. In PhenomPNR we incorporate precessing-binary NR results in two ways: (i) we produce the first NR-tuned model of the signal-based precession dynamics through merger and ringdown, and (ii) we extend a previous aligned-spin model, PhenomD, to include the effects of misaligned spins on the signal in the co-precessing frame. The NR calibration has been performed on 40 simulations of binaries with mass ratios between 1:1 and 1:8, where the larger black hole has a dimensionless spin magnitude of 0.4 or 0.8, and we choose five angles of spin misalignment with the orbital angular momentum. PhenomPNR has a typical mismatch accuracy within 0.1% up to mass-ratio 1:4, and within 1% up to mass-ratio 1:8.
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Inferring astrophysical information from gravitational waves emitted by compact binaries is one of the key science goals of gravitational-wave astronomy. In order to reach the full scientific potential of gravitational-wave experiments we require techniques to mitigate the cost of Bayesian inference, especially as gravitational-wave signal models and analyses become increasingly sophisticated and detailed. Reduced order models (ROMs) of gravitational waveforms can significantly reduce the computational cost of inference by removing redundant computations. In this paper we construct the first reduced order models of gravitational-wave signals that include the effects of spin-precession, inspiral, merger, and ringdown in compact object binaries, and which are valid for component masses describing binary neutron star, binary black hole and mixed binary systems. This work utilizes the waveform model known as IMRPhenomPv2. Our ROM enables the use of a fast reduced order quadrature (ROQ) integration rule which allows us to approximate Bayesian probability density functions at a greatly reduced computational cost. We find that the ROQ rule can be used to speed up inference by factors as high as 300 without introducing systematic bias. This corresponds to a reduction in computational time from around half a year to a half a day, for the longest duration/lowest mass signals. The ROM and ROQ rule are available with the main inference library of the LIGO Scientific Collaboration, LALInference.
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