Waveform systematics in gravitational-wave inference of signals from binary neutron star merger models incorporating higher order modes information
ORAL
Abstract
Accurate information from gravitational wave signals of binary neutron stars is important as these estimates are inputs for population inference and extreme matter studies. It is, hence, vital to use the most accurate and physically motivated models available for parameter estimation (PE) of BNS. These models are subject to waveform modeling uncertainty, and deviations can introduce biases in the parameter estimation performed using different models. In this work, we describe injection studies investigating these systematic differences between the two best waveform models available for BNS currently, NRHybSur3dq8Tidal, and TEOBResumS for sources observable by current ground-based detectors.
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Presenters
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Anjali Balasaheb Yelikar
Rochester Institute of Technology
Authors
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Anjali Balasaheb Yelikar
Rochester Institute of Technology
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Richard O'Shaughnessy
Rochester Institute of Technology
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Jacob A Lange
University of Texas at Austin
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Aasim Z Jan
University of Texas at Austin