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Inferring the maximum and minimum mass of merging neutron stars with gravitational waves

Chatziioannou, Katerina and Farr, Will M. (2020) Inferring the maximum and minimum mass of merging neutron stars with gravitational waves. Physical Review D, 102 (6). Art. No. 064063. ISSN 2470-0010. doi:10.1103/PhysRevD.102.064063. https://resolver.caltech.edu/CaltechAUTHORS:20200729-075455443

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Abstract

We show that the maximum and the minimum mass of merging neutron stars can be estimated with upcoming gravitational wave observations. We simulate populations of binary neutron star signals and model their mass distribution including upper and lower cutoffs. The lower (upper) limit can be measured to ∼0.2 (0.1)  M⊙ with 50 detections if the mass distribution supports neutron stars with masses close to the cutoffs. The upper mass limit informs about the high-density properties of the neutron star equation of state, while the lower limit signals the divide between neutron stars and white dwarfs.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1103/PhysRevD.102.064063DOIArticle
https://arxiv.org/abs/2005.00482arXivDiscussion Paper
ORCID:
AuthorORCID
Chatziioannou, Katerina0000-0002-5833-413X
Farr, Will M.0000-0003-1540-8562
Additional Information:© 2020 American Physical Society. Received 1 May 2020; accepted 20 August 2020; published 25 September 2020. We thank Hsin-Yu Chen, Paul Lasky, Cole Miller, and Eric Thrane for useful discussions. We thank Phil Landry and Bernard Whiting for carefully reading the manuscript. The Flatiron Institute is supported by the Simons Foundation. Software: matplotlib [71], stan [72], numpy [73], scipy [74], and astropy [75,76].
Funders:
Funding AgencyGrant Number
Simons FoundationUNSPECIFIED
Issue or Number:6
DOI:10.1103/PhysRevD.102.064063
Record Number:CaltechAUTHORS:20200729-075455443
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20200729-075455443
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:104630
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:29 Jul 2020 15:53
Last Modified:02 Sep 2021 21:53

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