Barack, Leor and Cutler, Curt
(2004)
LISA capture sources: approximate waveforms, signal-to-noise ratios, and parameter estimation accuracy.
*Physical Review D*, 69 (8), 082005-[24pp].
(doi:10.1103/PhysRevD.69.082005).

## Abstract

Captures of stellar-mass compact objects (COs) by massive ~10^{6} *M*_{☉} black holes (MBHs) are potentially an important source for LISA, the proposed space-based gravitational-wave (GW) detector. The orbits of the inspiraling COs are highly complicated; they can remain rather eccentric up until the final plunge, and display extreme versions of relativistic perihelion precession and Lense-Thirring precession of the orbital plane. The strongest capture signals will be ~10 times weaker than LISA's instrumental noise, but in principle (with sufficient computing power) they can be disentangled from the noise by matched filtering. The associated template waveforms are not yet in hand, but theorists will very likely be able to provide them before LISA launches. Here we introduce a family of approximate (post-Newtonian) capture waveforms, given in (nearly) analytic form, for use in advancing LISA studies until more accurate versions are available. Our model waveforms include most of the key qualitative features of true waveforms, and cover the full space of capture-event parameters (including orbital eccentricity and the MBH's spin). Here we use our approximate waveforms to (i) estimate the relative contributions of different harmonics (of the orbital frequency) to the total signal-to-noise ratio, and (ii) estimate the accuracy with which LISA will be able to extract the physical parameters of the capture event from the measured waveform. For a typical source (a 10 *M*_{☉} CO captured by a 10^{6} *M*_{☉} MBH at a signal-to-noise ratio of 30), we find that LISA can determine the MBH and CO masses to within a fractional error of ~10^{-4}, measure *S/M*^{2}$ (where *S* and *M* are the MBH's mass and spin) to within ~10^{-4}, and determine the sky location of the source to within ~10^{-3} stradians.

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