Bayesian time delay interferometry

Laser frequency noise (LFN) is the dominant source of expected in Interferometer Space Antenna (LISA) mission, at $\sim$7 orders magnitude greater than typical signal from gravitational waves (GWs). Time-delay interferometry (TDI) suppresses LFN to an acceptable level by linearly combining measurements individual spacecraft delayed durations that correspond their relative separations. Knowledge delay crucial for TDI effectiveness. The work reported here extends upon previous studies using data-driven methods inferring delays during post-processing raw phasemeter data, also known as ranging (TDIR). Our TDIR analysis uses Bayesian designed ultimately be included LISA data model part a "Global Fit" pipeline. Including Global Fit produces GW inferences which are marginalized over uncertainty separations and allows independent estimation orbits. We demonstrate Markov Chain Monte Carlo (MCMC) six time-independent required rigidly rotating approximation configuration (TDI 1.5) simulated data. MCMC fractional interpolation (FDI) digitally phase meter we study sensitivity filter length. Varying levels complexity covariance matrix examined. Delay estimations found result suppression well below secondary noises constraints on armlengths $\mathcal{O}(30)\ {\rm cm}$ ${\sim}2.5\ Gm}$ baseline.