Measuring the primordial gravitational wave background in the presence of other stochastic signals. (arXiv:2101.02713v2 [gr-qc] UPDATED)
<a href="http://arxiv.org/find/gr-qc/1/au:+Poletti_D/0/1/0/all/0/1">Davide Poletti</a>
Standard methodologies for the extraction of the stochastic gravitational
wave background (SGWB) from auto- or cross-correlation of interferometric
signals often involve the use of a filter function. The standard optimal filter
maximizes the signal-to-noise ratio (SNR) between the total SGWB and the noise.
We derive expressions for the optimal filter and SNR in the presence of a
target SGWB plus other unwanted components. We also generalize the methodology
to the case of template-free reconstruction. The formalism allows to easily
perform analyses and forecasts that marginalize over foreground signals, such
as the typical $Omega_{rm GW} propto f^{2/3}$ background arising from binary
coalescence. We demonstrate the methodology with the LISA mission and discuss
possible extensions and domains of application.
Standard methodologies for the extraction of the stochastic gravitational
wave background (SGWB) from auto- or cross-correlation of interferometric
signals often involve the use of a filter function. The standard optimal filter
maximizes the signal-to-noise ratio (SNR) between the total SGWB and the noise.
We derive expressions for the optimal filter and SNR in the presence of a
target SGWB plus other unwanted components. We also generalize the methodology
to the case of template-free reconstruction. The formalism allows to easily
perform analyses and forecasts that marginalize over foreground signals, such
as the typical $Omega_{rm GW} propto f^{2/3}$ background arising from binary
coalescence. We demonstrate the methodology with the LISA mission and discuss
possible extensions and domains of application.
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