LISA auto-correlation SNR equals the square root of T_obs times the integral of (signal/(noise+signal))^2 and is therefore bounded by sqrt(T_obs(f_max-f_min)).
Full analytical formulas for frequency response of space-based gravitational wave detectors
2 Pith papers cite this work. Polarity classification is still indexing.
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abstract
The discovery of gravitational waves, which are ripples of space-time itself, opened a new window to test general relativity, because it predicts that there are only plus and cross polarizations for gravitational waves. For alternative theories of gravity, there may be up to six polarizations. The measurement of the polarization is one of the major scientific goals for future gravitational wave detectors. To evaluate the capability of the detector, we need to use the frequency dependent response functions averaged over the source direction and polarization angle. We derive the full analytical formulas of the averaged response functions for all six possible polarizations and present their asymptotic behaviors based on these analytical formulas. Compared with the numerical simulation, the full analytical formulas are more efficient and valid for any equal-arm interferometric gravitational wave detector without optical cavities in the arms and for a time-delay-interferometry Michelson combination.
fields
gr-qc 2years
2026 2representative citing papers
Dynamic LISA/Taiji sensitivity curves exhibit 20% low-frequency variation and 70% directional source-count variation relative to static models, with quadrant patterns at low frequencies.
citing papers explorer
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Signal-to-Noise Ratio Contours for LISA
LISA auto-correlation SNR equals the square root of T_obs times the integral of (signal/(noise+signal))^2 and is therefore bounded by sqrt(T_obs(f_max-f_min)).
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Construction of Sensitivity Curves for Dynamic LISA and Taiji
Dynamic LISA/Taiji sensitivity curves exhibit 20% low-frequency variation and 70% directional source-count variation relative to static models, with quadrant patterns at low frequencies.