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We perform an analysis of the binary neutron star coalescence event GW170817, to improve the inference of the properties of neutron stars. The observation of electromagnetic counterparts of the GW170817 event suggests that the event did not lead to the prompt formation to a black-hole. In this work, we first briefly overview different numerical techniques used to perform the numerical relativity simulations of binary-neutron stars followed by a review of the mass-ratio dependent fits for the threshold mass ( \(M_\textrm{thr}\) ), a characteristic mass used to classify the merger remnant. Finally, we classify the GW170817 LIGO-Virgo data sample into the prompt collapse to a black-hole using the q-dependent threshold mass fits to infer the properties of neutron stars.

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Improving Inference on Neutron Star Properties Using Information from Binary Merger Remnants

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  • 发表日期：

    2025年

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  • Tamanna Jain

摘要

We perform an analysis of the binary neutron star coalescence event GW170817, to improve the inference of the properties of neutron stars. The observation of electromagnetic counterparts of the GW170817 event suggests that the event did not lead to the prompt formation to a black-hole. In this work, we first briefly overview different numerical techniques used to perform the numerical relativity simulations of binary-neutron stars followed by a review of the mass-ratio dependent fits for the threshold mass ( \(M_\textrm{thr}\) ), a characteristic mass used to classify the merger remnant. Finally, we classify the GW170817 LIGO-Virgo data sample into the prompt collapse to a black-hole using the q-dependent threshold mass fits to infer the properties of neutron stars.