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.