Fully Data‐Driven Time‐Delay Interferometry with Time‐Varying Delays

Raw space-based gravitational-wave data like LISA's phase measurements are dominated by laser frequency noise. The standard technique to make this usable for science is time-delay interferometry (TDI), which cancels noise terms forming suitable combinations of delayed measurements. We recently introduced the basic concepts an alternative approach which, unlike TDI, does not rely on independent knowledge temporal correlations in dominant Instead, our automated Principal Component Interferometry (aPCI) processing only assumes that one can produce some linear temporally nearby regularly spaced measurements, cancel Then we let reveal those combinations. Our previous work relies simplifying additional assumption filters lead laser-noise-free streams time-independent. In LISA, however, these will vary as constellation armlengths evolve. Here, discuss a generalization aPCI concept compatible with still unmodeled but slowly varying covariance. Despite its independence any model, successfully mitigates below other noises' level, and sensitivity gravitational waves same state-of-the-art second-generation up 2\% error.