[eng] The first detection of gravitational waves (GWs) in 2015 [1] marked the beginning of an
ongoing revolution in astronomy and fundamental physics. Since then around 90 signals
have been detected as having astrophysical origin in the three observing runs O1-O3 [2–5]
and the just-started O4 [6]. After this current run, the international detector network will
receive further upgrades such as ESA’s LISA mission [7, 8], scheduled for launch in the
2030s.
One of the fundamental fields in GW data analysis is the estimation of the source parameters
using Bayesian inference, where theoretical waveform models are used as templates for
the incoming signals. Those models have achieved high accuracy with current LIGOVirgo-KAGRA detectors; however, further improvements will be required to match future
detectors’ sensitivities.
In this work, I test current Inspiral-Merger-Ringdown (IMR) waveforms against the LISA
space mission scientific requirements [9] for massive black hole binaries (MBHB). These
requirements set an upper bound on the permissible errors for parameter estimation (PE)
and become a challenge for theoretical models. Apart from calibration inaccuracies of the
detectors, the error has two main contributions: waveform systematics and the statistical
error of the measurement. The former is estimated by computing the mismatch between
the model and another one which is considered the template; whilst the statistical error
can be quickly estimated with the Fisher Information Matrix approach. Then, they are
compared with the observational requirements. Furthermore, in some cases, a full PE run
is performed in order to check the consistency of the previous error estimates.
Our purpose is to guide future waveform modeling tasks and black hole numerical simulations in order to improve current IMR models for future observing periods.