Statistical and systematic uncertainties in extracting the source properties of neutron star - black hole binaries with gravitational waves
Yiwen Huang, Carl-Johan Haster, Salvatore Vitale, Vijay Varma,, Francois Foucart, Sylvia Biscoveanu

TL;DR
This paper assesses the statistical and systematic uncertainties in extracting properties of neutron star-black hole binaries from gravitational wave signals, highlighting the impact of waveform modeling and signal-to-noise ratio on measurement accuracy.
Contribution
It introduces a hybrid waveform approach combining numerical relativity and surrogate models to evaluate uncertainties in source parameter estimation.
Findings
Statistical uncertainties dominate at SNR 30, systematic errors become comparable at SNR 70.
Masses and mass ratios are measured precisely but with some inaccuracy at high SNR.
Neutron star tidal deformability can be constrained at high SNR, but neutron star spin remains poorly constrained.
Abstract
Gravitational waves emitted by neutron star black hole mergers encode key properties of neutron stars - such as their size, maximum mass and spins - and black holes. However, the presence of matter and the high mass ratio makes generating long and accurate waveforms from these systems hard to do with numerical relativity, and not much is known about systematic uncertainties due to waveform modeling. We simulate gravitational waves from neutron star black hole mergers by hybridizing numerical relativity waveforms produced with the SpEC code with a recent numerical relativity surrogate NRHybSur3dq8Tidal. These signals are analyzed using a range of available waveform families, and statistical and systematic errors are reported. We find that at a network signal-to-noise ratio (SNR) of 30, statistical uncertainties are usually larger than systematic offsets, while at an SNR of 70 the two…
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Taxonomy
TopicsPulsars and Gravitational Waves Research · Geophysics and Gravity Measurements · Geophysics and Sensor Technology
