Gravitational wave data analysis implications of TaylorEt inspiral approximants for ground-based detectors: the non-spinning case

Details Gravitational wave data analysis implications of TaylorEt inspiral approximants for ground-based detectors: the non-spinning case Gravitational wave data analysis implications of TaylorEt inspiral approximants for ground-based detectors: the non-spinning case

2008-07-15

arxiv.org/abs/0807.2400v2

Astronomy and Astrophysics

Astrophysics

General Relativity and Quantum Cosmology

3 figures, 5 tables

Scientific paper

A new family of restricted post-Newtonian-accurate waveforms, termed TaylorEt approximants, was recently proposed for searching gravitational wave (GW) signals from inspiraling non-spinning compact binaries having arbitrary mass-ratios. We perform detailed fitting factor (FF) studies to probe if the TaylorEt (3.5PN) signals for non-spinning comparable mass compact binaries can be effectually and faithfully searched with TaylorT1, TaylorT4, and TaylorF2 (3.5PN) templates in LIGO, Advanced LIGO, and Virgo interferometers. We observe that a good fraction of the templates, which by choice are from TaylorT1, TaylorT4, and TaylorF2 (3.5PN) families, have FF <~ 0.97 and substantial biases for the estimated total-mass against the fiducial TaylorEt (3.5PN) signals for equal-mass systems. Both these observations can bear on the detectability of a signal. TaylorEt (3.5PN) signals with mass-ratios of a third or a quarter yield high FFs against those same template banks, but at the expense of inviting large systematic errors in the estimated values of their total mass and symmetric mass-ratio. In general, the aforementioned templates are found to be increasingly {\it unfaithful} with respect to a TaylorEt signal as one increases the total mass of the inspiraling system. We also observe that the amount of bias in the estimated mass varies with the (noise power spectral density of the) detector. This can be of some concern for multi-detector searches, which check for consistency in the estimated masses of concurrent triggers in their data. (Abridged)

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