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Numerical simulations of black-hole binaries (gravity)

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  • Full or part time
    Prof Mark Hannam
    Prof Stephen Fairhurst
  • Application Deadline
    No more applications being accepted
  • Competition Funded PhD Project (European/UK Students Only)
    Competition Funded PhD Project (European/UK Students Only)

Project Description

Numerical solutions of the Einstein equations for the last orbits and merger of two black holes are essential to model the gravitational-wave signal from such systems, which are the prime source for gravitational-wave observations with Advanced LIGO and Virgo. Our current numerical codes allow us to simulate systems of moderate mass ratios, and for black holes with moderate spins. Improved numerical techniques, coordinate conditions and initial data will allow us to study systems with far higher mass ratios and spins. These systems are interesting to study for their physical properties alone, as well as being essential for modelling generic-binary waveforms for gravitational-wave applications. A number of research directions are possible, based on the potential improvements mentioned above, as well as the study of the physics of black-hole mergers for specific configurations -- the details of ringdown waveforms, black-hole recoil, and precession effects.

Funding Notes

The Science Technology Facilities Council welcomes applications from both UK and EU applicants.
Full awards (tuition fees plus maintenance stipend) are open to UK Nationals and EU students who can satisfy UK residency requirements. For more information visit: http://www.stfc.ac.uk/funding/studentships/studentship-terms-conditions-guidance/student-eligibility-requirements/
The research project listed above is in competition with other projects for 2017/18; studentships will be awarded to the highest ranked applicants from all applications received. We reserve the right to close applications early should sufficient applications be received.

Related Subjects

How good is research at Cardiff University in Physics?

FTE Category A staff submitted: 19.50

Research output data provided by the Research Excellence Framework (REF)

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