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Pre/Post-Merger Consistency Test for Gravitational Signals from Binary Neutron Star Mergers

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  • Additional Information
    • Contributors:
      Benhar, Omar; Sedrakian, Armen
    • Publication Date:
      2023
    • Collection:
      Digital Library Thüringen
    • Abstract:
      Gravitational waves from binary neutron star (BNS) mergers can constrain nuclear models, predicting their equation of state (EOS). Matter effects on the inspiral-merger signal are encoded in the multipolar tidal polarizability parameters, whose leading order combination is sufficient to capture, with high accuracy, the key features of the merger waveform. Similar EOS-insensitive relations exist for the post-merger signal and can be used to model the emissions from the remnant. Several works suggested that the appearance of new degrees of freedom in high-density post-merger matter can be inferred by observing a violation of these EOS-insensitive relations. Here, we demonstrate a Bayesian method to test such an EOS-insensitive relation between the tidal polarizability parameters (or any other equivalent parameter) and the dominant post-merger frequency using information from the pre-and-post-merger signal. Technically, the method is similar to the inspiral-merger-ringdown consistency tests of General Relativity with binary black holes. However, differently from the latter, BNS pre/post-merger consistency tests are conceptually less informative and they only address the consistency of the assumed EOS-insensitive relation. Specifically, we discuss how such tests cannot conclusively discriminate between an EOS without respecting such a relation and the appearance of new degrees of freedom (or phase transitions) in high-density matter.
    • File Description:
      8 Seiten
    • Relation:
      Particles -- Particles -- 2571-712X -- 2926939-8; https://doi.org/10.3390/particles6030045
    • Accession Number:
      10.3390/particles6030045
    • Online Access:
      https://doi.org/10.3390/particles6030045
      https://nbn-resolving.org/urn:nbn:de:gbv:27-dbt-20230808-190421-007
      https://www.db-thueringen.de/receive/dbt_mods_00058397
      https://www.db-thueringen.de/servlets/MCRFileNodeServlet/dbt_derivate_00061145/particles-06-00045.pdf
    • Rights:
      https://creativecommons.org/licenses/by/4.0/ ; public ; info:eu-repo/semantics/openAccess
    • Accession Number:
      edsbas.F4B6A30B