In this thesis, Bayesian inference methods are used to set constraints on the speed of sound and hence the equation of state of neutron star matter based on recent multimessenger data in combination with limiting conditions from theoretical calculations. The speed of sound must increase rapidly to ensure the stability of the heaviest known pulsars, which limits the possible appearance of strong phase transitions in neutron star cores. Furthermore, we develop a novel neural inference method that can infer the equation of state directly from detector observations.
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In this thesis, Bayesian inference methods are used to set constraints on the speed of sound and hence the equation of state of neutron star matter based on recent multimessenger data in combination with limiting conditions from theoretical calculations. The speed of sound must increase rapidly to ensure the stability of the heaviest known pulsars, which limits the possible appearance of strong phase transitions in neutron star cores. Furthermore, we develop a novel neural inference method that...
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