Systematic biases in parameter estimation on LISA binaries: The effect of excluding higher harmonics for non-spinning binaries
Sophia Yi, Francesco Iacovelli, Sylvain Marsat, Digvijay Wadekar, Emanuele Berti

TL;DR
This paper investigates how excluding higher-order multipole modes in waveform templates causes significant biases in parameter estimation of massive black hole binaries with LISA, especially for high-mass events, and proposes methods to predict and mitigate these biases.
Contribution
It demonstrates the severity of systematic biases from missing higher modes in LISA MBHB signals and introduces efficient methods to predict and address these biases.
Findings
Biases are severe for total mass > 10^6 M_sun.
Likelihood optimization can predict biases efficiently.
Including modes with l≥5 improves parameter estimation accuracy.
Abstract
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 detected signal will be limited by the accuracy of the waveform templates we use. In this paper, we explore the systematic biases that arise in parameter estimation if we use waveform templates that do not model radiation in higher-order multipoles. This is an important consideration for the large fraction of high-mass events expected to be observed with LISA. We examine how the biases change for MBHB events with different total masses, mass ratios, and inclination angles. We find that systematic biases due to insufficient mode content are…
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Taxonomy
TopicsPulsars and Gravitational Waves Research · Radio Astronomy Observations and Technology · Adaptive optics and wavefront sensing
