Depicting a Black Hole Merger: A Bridge Between Einstein Toolkit and GYOTO

In this project we create a conversion tool for using numerical general relativity simulations done in Einstein Toolkit in the numerical relativity ray tracer tool General relativitY Orbit Tracer of Observatoire de Paris(GYOTO). Due to the different formalisms used by Einstein Toolkit and GYOTO, the numerical relativity framework Langage Objet pour la RElativité NumériquE(LORENE) was used to bridge between the two. Simulations of a isotropic Schwarzschild metric and a binary black hole merger initialized with a two puncture method were used as test data to evaluate the tool. The spectral formalism used by LORENE has a spherical topology, meaning that a custom splitting function had to be devised to split the binaries into separate, pseudo-spherical spacetimes. We used Python to read and interpolate the data from Einstein Toolkit, and to call on a separate C-code using LORENE to take care of the spectral transformation. We showed that the process of reading and interpolating the Einstein Toolkit data will lead to numerical errors at order 10^{-5}. This error was also manifest in the final ray tracing. With proper parameterization, the spectral transformation did not show any major additions of error, and could in some cases smooth out errors. We showed that it was possible to transform the black hole binary, but at a much greater computational cost. Results without using the splitting function was also shown to lead to artifacts in the transformed metric. We used drift in the photon momentum norm from a base line of zero to measure errors in the ray tracing. With this we showed that the numerical errors when using the Schwarzschild metric in GYOTO was about 0-10^{3} times higher than ray tracing done with a standard metric made with LORENE, which only was an error increase of 10^{-3} in absolute terms. To use the black hole binary metric in GYOTO, small changes to GYOTO are still needed, and we weren't able to do ray tracing using this metric. We conclude that by using our tool we successfully used GYOTO with a single black hole metric simulated in Einstein Toolkit, and that the tool is capable of transforming black hole binary metric for when this function is implemented in GYOTO