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Simulating Binary Neutron Star Mergers

  • Tim Dietrich*
  • , Bernd Brügmann
  • , Edoardo Giangrandi
  • , Henrique Leonhard Gieg
  • , Nina Kunert
  • , Ivan Markin
  • , Vsevolod Nedora
  • , Anna Neuweiler
  • , Henrik Rose
  • , Peter Tsun Ho Pang
  • , Federico Schianchi
  • , Ashwin Shirke
  • , Maximiliano Ujevic
  • *Corresponding author for this work
  • Friedrich Schiller University Jena
  • University of Potsdam
  • University of Coimbra
  • Universidade Federal do ABC

Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

Abstract

To date, about one hundred gravitational-wave events have been detected. Among them, the binary neutron star merger GW170817 was of particular significance since, in addition to gravitational waves, also electromagnetic signatures were observed. As the international network of gravitational-wave detectors has recently restarted, more multi-messenger detections are expected in the coming year. Due to the strong gravitational fields during the final stages of the coalescence, the study of compact binary merger requires numerical-relativity simulations that solve Einstein’s Field Equations. These simulations heavily rely on high-performance computing facilities such as HAWK. We use for our research the numerical-relativity code BAM and explore the intricate relation between extreme spacetime and matter beyond the density of atomic nuclei. We further developed a framework that allows us to correlate observations with theoretical models using Bayesian methods. In this way, we can extract valuable physical information from the detected signals and explore the properties of matter on subatomic and cosmic scales.

Original languageEnglish
Title of host publicationHigh Performance Computing in Science and Engineering '23
Subtitle of host publicationTransactions of the High Performance Computing Center, Stuttgart (HLRS) 2023
EditorsThomas Ludwig, Peter Bastian, Michael M. Resch
PublisherSpringer
Pages29-40
Number of pages12
ISBN (Electronic)9783031913129
ISBN (Print)9783031913112
DOIs
Publication statusPublished - 24 Jan 2026

Bibliographical note

Publisher Copyright:
© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.

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