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Gravitational waves from binary black hole mergers

Principal Investigator: Prof. Denis Pollney
Institution: Rhodes University
Domain: Astrophysics

Black hole mergers are the most prominent sources of gravitational waves (GW), and have been the subject of much excitement in recent years. In 2015, the first observation of a pair of colliding black holes was observed by the LIGO gravitational wave detector and was the subject of the 2017 Nobel Prize in Physics. Since then, a half dozen other merger events have been recorded delivering a wealth of information about these object to astrophysicists.

The Rhodes Mathematics Department is part of an international collaboration developing, running, and interpreting computer models of black holes in order to better understand their properties and their gravitational wave emissions. There is a great deal of work to be done to understand subtle features of GW signals which may to a new understanding of our classical theory of gravity, including the possibility or modifications to the century old theory of general relativity.

Our group has focussed on studying GWs from systems that may mimic the signatures of binary black holes. Objects called “boson stars” represent a particularly simple form of matter that can yield very similar signals. By characterizing subtle differences between signals generated by these objects we hope to remove an important source of ambiguity and confirming our classical understanding of gravity.

High accuracy demands large computational resources. Expanded fully, the Einstein equations of general relativity involve 20 000 computations at each point within a spacetime. As a result, these simulations are carried out at some of the world’s largest supercomputers, including the one at the CHPC. Our simulation code, developed with collaborators around the world, is contributing to an international effort to understand these systems. And locally developed techniques, including “characteristic matching” — a method of evolving spacetimes without boundaries — are leading to new levels of precision in our ability to model black hole systems.

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