Parameter Estimation Method that Directly Compares Gravitational Wave Observations to Numerical Relativity

TLDR: This study of this new parameter estimation method demonstrates that it can quantify and understand the systematic and statistical error, and allows us to use higher order modes from numerical relativity simulations to better constrain the black hole binary parameters.

Abstract: We present and assess a Bayesian method to interpret gravitational wave signals from binary black holes Our method directly compares gravitational wave data to numerical relativity (NR) simulations In this study, we present a detailed investigation of the systematic and statistical parameter estimation errors of this method This procedure bypasses approximations used in semianalytical models for compact binary coalescence In this work, we use the full posterior parameter distribution for only generic nonprecessing binaries, drawing inferences away from the set of NR simulations used, via interpolation of a single scalar quantity (the marginalized log likelihood, lnL) evaluated by comparing data to nonprecessing binary black hole simulations We also compare the data to generic simulations, and discuss the effectiveness of this procedure for generic sources We specifically assess the impact of higher order modes, repeating our interpretation with both l ≤ 2 as well as l ≤ 3 harmonic modes Using the l ≤ 3 higher modes, we gain more information from the signal and can better constrain the parameters of the gravitational wave signal We assess and quantify several sources of systematic error that our procedure could introduce, including simulation resolution and duration; most are negligible We show through examples that our method can recover the parameters for equal mass, zero spin, GW150914-like, and unequal mass, precessing spin sources Our study of this new parameter estimation method demonstrates that we can quantify and understand the systematic and statistical error This method allows us to use higher order modes from numerical relativity simulations to better constrain the black hole binary parameters