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Published December 15, 2017 | Published + Accepted Version
Journal Article Open

Inferring the post-merger gravitational wave emission from binary neutron star coalescences

Abstract

We present a robust method to characterize the gravitational wave emission from the remnant of a neutron star coalescence. Our approach makes only minimal assumptions about the morphology of the signal and provides a full posterior probability distribution of the underlying waveform. We apply our method on simulated data from a network of advanced ground-based detectors and demonstrate the gravitational wave signal reconstruction. We study the reconstruction quality for different binary configurations and equations of state for the colliding neutron stars. We show how our method can be used to constrain the yet-uncertain equation of state of neutron star matter. The constraints on the equation of state we derive are complementary to measurements of the tidal deformation of the colliding neutron stars during the late inspiral phase. In the case of nondetection of a post-merger signal following a binary neutron star inspiral, we show that we can place upper limits on the energy emitted.

Additional Information

© 2017 American Physical Society. Received 31 October 2017; published 26 December 2017. We thank Carl-Johan Haster and Aaron Zimmerman for numerous engaging conversations. We thank Christopher P. L. Berry for sharing with us the fit for the total mass measurement error as a function of the SNR computed in Ref. [74]. We thank Will Farr and Jonah Kanner for comments on the analysis and the manuscript. J. C. acknowledges support from NSF Grants No. PHYS-1505824 and No. PHYS-1505524. A. B. acknowledges support by the Klaus Tschira Foundation. M. M. and N. C. acknowledge support from NSF Grant No. PHY-1306702. This research was done using resources provided by the Open Science Grid [76,77], which is supported by the National Science Foundation Grant No. 1148698, and the U.S. Department of Energy's Office of Science. This research was also supported in part through research cyberinfrastructure resources and services provided by the Partnership for an Advanced Computing Environment at the Georgia Institute of Technology [78]. Figures in this manuscript were produced using matplotlib [79].

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Published - PhysRevD.96.124035.pdf

Accepted Version - 1711.00040.pdf

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August 19, 2023
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