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Simulating Binary Neutron Star Mergers

Title: Simulating Binary Neutron Star Mergers
Authors: Dietrich, Tim; Brügmann, Bernd; Giangrandi, Edoardo; Gieg, Henrique Leonhard; Kunert, Nina; Markin, Ivan; Nedora, Vsevolod; Neuweiler, Anna; Rose, Henrik; Pang, Peter Tsun Ho; Schianchi, Federico; Shirke, Ashwin; Ujevic, Maximiliano; Sub Subatomic Physics (SAP); Sub GRASP; Gravitational and Subatomic Physics (GRASP); Ludwig, Thomas; Bastian, Peter; Resch, Michael M.
Publication Year: 2026
Subject Terms: Taverne; General Mathematics; General Computer Science; General Physics and Astronomy; General Chemistry; General Engineering
Description: 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.
Document Type: book part
File Description: application/pdf
Language: English
Relation: https://dspace.library.uu.nl/handle/1874/483505
Availability: https://dspace.library.uu.nl/handle/1874/483505
Rights: info:eu-repo/semantics/EmbargoedAccess
Accession Number: edsbas.6D2DBE29
Database: BASE