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Graphical Processing of Geodesic Propagation in Python by Imbens, Frank is a scholarly article available to read on EtoBox.

What is Graphical Processing of Geodesic Propagation in Python about?

Black holes and other compact objects are powerful tools to observationally test Einsteins theory of General Relativity. We develop raytracing code to create visual images of compact objects that are solutions of Einsteins field equations. These include Kerr black holes and Manko-Novikov spacetimes with extra independent multipole moments. Using parallel processing on a graphical processing unit we can trace the millions of geodesics required to create such images of compact objects. The loss of symmetry in Manko-Novikov spacetime leads to strange features such as chaotic regions in the dynamics. We also analyse other properties of geodesics, such as their exit times from the strong field nearby the object, their redshift, or behaviour near capture regions. We also add objects such as accretion disks to our spacetime, and determine how they are lensed by the object. The main draw of this code is it's efficiency and simplicity, as it allows for creating these images even on older hardware, while still allowing any time independent metric to be studied. The code is publicly available on github.

Author

Imbens, Frank

Published

2023

Language

EN