Marginalizing over Noise Power Spectrum Uncertainty in Gravitational-Wave Parameter Estimation*

The traditional gravitational wave parameter estimation process relies on sequential estimation of noise properties and binary parameters, which assumes the noise variance is perfectly known. In this talk I will describe an analysis that simultaneously models the noise power spectrum and the signal, thus marginalizing over uncertainty in the noise. I will compare the sequential estimation method to the simultaneous method on events from GWTC-2 and discuss the effect on inferred parameters. I will argue that at current sensitivities, noise power spectrum uncertainty is a subdominant effect compared to other sources of uncertainty such as waveform systematics.