Defines peak-integrated sensitivity curves (PISCs) that fold in the expected spectral shape of gravitational waves from cosmological phase transitions and supplies semianalytical fits plus public data for major detectors.
Sensitivity curves for spaceborne gravitational wave interferometers
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abstract
To determine whether particular sources of gravitational radiation will be detectable by a specific gravitational wave detector, it is necessary to know the sensitivity limits of the instrument. These instrumental sensitivities are often depicted (after averaging over source position and polarization) by graphing the minimal values of the gravitational wave amplitude detectable by the instrument versus the frequency of the gravitational wave. This paper describes in detail how to compute such a sensitivity curve given a set of specifications for a spaceborne laser interferometer gravitational wave observatory. Minor errors in the prior literature are corrected, and the first (mostly) analytic calculation of the gravitational wave transfer function is presented. Example sensitivity curve calculations are presented for the proposed LISA interferometer. We find that previous treatments of LISA have underestimated its sensitivity by a factor of $\sqrt{3}$.
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The work provides the first quantitative characterization of how spacecraft orbit uncertainties and velocity mismodeling propagate into LISA gravitational-wave response mismatches and parameter biases.
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New Sensitivity Curves for Gravitational-Wave Signals from Cosmological Phase Transitions
Defines peak-integrated sensitivity curves (PISCs) that fold in the expected spectral shape of gravitational waves from cosmological phase transitions and supplies semianalytical fits plus public data for major detectors.
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Impact of Spacecraft Orbit Uncertainties and Velocity Mismodeling on the LISA Gravitational-Wave Response
The work provides the first quantitative characterization of how spacecraft orbit uncertainties and velocity mismodeling propagate into LISA gravitational-wave response mismatches and parameter biases.