Systematic biases from the exclusion of higher harmonics in parameter estimation on massive LISA binaries

The remarkable sensitivity achieved by the planned Laser Interferometer Space Antenna (LISA) will allow us to observe gravitational-wave signals from the mergers of massive black hole binaries (MBHBs) with signal-to-noise ratio (SNR) in the hundreds or even thousands. At such high SNR, our ability to precisely infer the parameters of an MBHB from the signal will be limited by the accuracy of waveform templates we use. We explore the systematic biases that arise in parameter estimation due to using waveform templates that do not model radiation in higher-order harmonics. We examine the biases over a range of parameter space, observing how they change for MBHB events with different total masses, mass ratios, and inclination angles. We find that systematic biases due to insufficient mode content are severe for events with total redshifted mass above ~10⁶M_⊙. We then compare several methods of predicting such systematic biases without having to perform full Bayesian parameter estimation. With at least one of these methods (involving Nelder-Mead optimization techniques), we are able to cheaply predict systematic biases for many events with remarkable speed and accuracy.