Factorized Parameter Estimation for Real-Time Gravitational Wave Inference

Understand

We present a parameter estimation framework for gravitational wave (GW) signals that brings together several ideas to accelerate the inference process.

• First, we use the relative binning algorithm to evaluate the signal-to-noise-ratio timeseries in each detector for a given choice of intrinsic parameters.
• Second, we decouple the estimation of the intrinsic parameters (such as masses and spins of the components) from that of the extrinsic parameters (such as distance, orientation, and sky location) that describe a binary compact object coalescence.
• We achieve this by semi-analytically marginalizing the posterior distribution over extrinsic parameters without repeatedly evaluating the waveform for a fixed set of intrinsic parameters.