PhD Tesis defense
On the 10th of october, at 10:00 , in the classroom of the mathematics faculty, Burjassot, will take place the PhD thesis defense of Miquel Miravet Tenés, that has been supervised by Pablo Cerdá Durán and José A. Font Roda.
Abastract:
"Turbulence modelling and gravitational-wave data analysis for binary neutron star mergers"
The plethora of gravitational-wave observations from several astronomical systems is changing our understanding of the Universe at an unprecedented rate. More concretely, the multimessenger observations of binary neutron star mergers have provided important information about matter at extreme densities, the generation of short gamma-ray bursts, the production of heavy elements, and the rate of expansion of the Universe. The understanding of the complex physics involved in this astrophysical scenario has been expanded thanks to the use of numerical simulations. Realistic simulations of binary neutron star mergers can provide gravitational-wave signals that can be directly compared to real detections. The study of the postmerger gravitational-wave signal can put constraints on the equation of state and give information about the dynamics and stability of the merger remnant. This thesis presents a comprehensive study of the magnetohydrodynamical turbulence triggered by the main instabilities developed during and after the merger of two neutron stars: the Kelvin-Helmholtz instability and the magnetorotational instability. Moreover, this thesis provides several applications of unmodelled reconstructions of binary neutron star postmerger signals, and a new approach to rapidly classify gravitational-wave sources. The first part of the thesis focuses on the development of a new model for turbulence in binary neutron star mergers. This new model, which consists in solving evolution equations for turbulent energy densities, aims to reproduce the effects of small-scale physics with moderate resolution. Moreover, this part of the thesis presents a new study of the saturation mechanism of the magnetorotational instability. The second part of the thesis is dedicated to the analysis of gravitational-wave signals from the postmerger phase of binary neutron star mergers. Due to the stochastic nature of the signal during that phase, unmodelled reconstructions are applied to study the inference of inertial modes and the detectability of differences in the treatment of thermal effects with the equation of state. Furthermore, a new machine learning approach to rapidly classify compact binary sources of gravitational waves is presented. This new scheme aims to provide more faithful information about the gravitational-wave source to perform electromagnetic follow-up observations. The findings of this thesis enhance our understanding of the instabilities that play a role in binary neutron star mergers by developing turbulence that can have important consequences on the stability of the merger remnant. Moreover, the work on gravitational-wave data analysis has implications for future applications of gravitational-wave astronomy to study the equation of state of neutron star matter, and multimessenger observations of compact binary systems.
