This is my PhD thesis was written in 2019-2021 and defended in 2022.
The thesis focuses on binary neutron star mergers (BNS) and specifically on the analysis of the BNS merger simulations performed with numerical relativity, i.e.,g general relativistic hydrodynamic code WhiskiTHC written and maintained by Prof. David Radice who co-supervised my thesis.
In this thesis, I developed a big data processing and analysis pipeline for the simulation data. The pipeline is located at this repository. The code is written in Python 3, employing agile philosophy, lazy evaluation and object-orientated infrastructure.
The code can be easily generalized to process simulations generated with other numerical relativity simulations, as was done for the BAM code. The implementation can be found in this repository.
The pipeline has been used in numerous scientific publications to extract valuable, publication-ready information and plots from simulations
Besides the hydrodynamics and early evolution of the BNS merger and postmerger, the thesis focuses on the electromagnetic counterparts to BNS mergers.
Specifically, kilonova is discussed and modeled using semi-analytic multicomponent code MKN developed by Prof. Albino Perego who also co-supervised my PhD thesis.
One of the findings of my research is that a newly discovered outflow from the postmerger remnant can be the source of blue emission seen in GRB170817A/KN2017gfo, the famous multimessenger event observed in 2017.
Finally, in this thesis, I developed a code to model non-thermal emission from matter ejected at BNS mergers that move through the interstellar medium and shock it (so-called collisionless shocks). This is generally called an afterglow. For a gamma-ray burst, it is a gamma-ray burst afterglow and for a kilonova, it would be a kilonova afterglow.
The code, named PyBlastAfterglow can be found in this repository. It is written in Python 3 and has an object-orientated infrastructure. It is malty-physics, meaning that I implemented several physics modules that perform the same task but have different levels of approximation and numerical complexity. The code includes a set of unit-tests and code-level tests.
The discovery that I made applying this code to the ejecta from the BNS merger simulations I was working with is that the late-time emission GRB170817A event can be explained self-consistently and, furthermore, additional new information about this event can be learned. This was published in a highly regarded APJL journal and was considered for publication in Nature. This project and this code were the foundation of my future research done at Max Plank Institute which can be found on my page.