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LISA Gravitational Wave Sources in A Time-Varying Galactic Stochastic Background
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A unique challenge for data analysis with the Laser Interferometer Space Antenna (LISA) is that the noise backgrounds from instrumental noise and astrophysical sources will change significantly over both the year and the entire mission. Variations in the noise levels will be on time scales comparable to, or shorter than, the time most signals spend in the detector's sensitive band. The variation in the amplitude of the galactic stochastic GW background from galactic binaries as the antenna pattern rotates relative to the galactic center is a particularly significant component of the noise variation. LISA's sensitivity to different source classes will therefore vary as a function of sky location and time. The variation will impact both overall signal-to-noise and the efficiency of alerts to EM observers to search for multi-messenger counterparts.
Forward citations
Cited by 4 Pith papers
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Non-stationary noise in gravitational wave analyses: The wavelet domain noise covariance matrix
For slowly varying detector noise, the Wilson-Daubechies-Meyer wavelet noise covariance matrix is approximately diagonal, with off-diagonal terms controlled by the time and frequency derivatives of the dynamic spectral model.
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Enhancing Taiji's Parameter Estimation under Non-Stationarity: a Time-Frequency Domain Framework for Galactic Binaries and Instrumental Noises
A time-frequency (STFT) Bayesian framework improves Taiji Galactic binary and noise parameter estimation under non-stationary noise compared with frequency-domain analysis.
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Modeling non-stationary noise: applications in gravitational wave astronomy
A positive dynamic spectrum S(f,t) generalizes the stationary power spectrum by defining Gramian closed-form noise covariances in Fourier and Wilson-Daubechies wavelet bases for gravitational wave data.
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An explicit and differentiable Wilson-Daubechies-Meyer transform for gravitational-wave data analysis
Open-source WDM transform package with JAX support and numerical validation of equivalence to frequency-domain likelihoods for a LISA binary under stationary noise.
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