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Conferències al DAA. Xerrada a càrrec de l'investigador Sergi Navarro Albalat, Physics Department, University of Texas, EE.UU.

  • 10 de desembre de 2020
Imatge conferència Sergi Navarro

Conferències al DAA. Xerrada a càrrec de l'investigador Sergi Navarro Albalat, Physics Department, University of Texas, EE.UU.

Lloc: Saló de Graus Lise Meitner, Facultat de Física, Bloc C, planta baixa, a Burjassot.

Dia: dimecres 16 de desembre de 2020. Hora: 12:00.

 

"Using numerical relativity simulations to inform gravitational self-force methods."

 

ABSTRACT:

Numerical relativity simulations are the tool we have to solve the merger of two black holes of intermediate mass ratios in the regime of strong gravitational field, where analytic approximations fail. Interpreting the data from the simulations in the form of gravitational waves, and using it to create a waveform data base is crucial if we want to cross compare with the the experimentally observed gravitational waves by LIGO-Virgo (and LISA in the coming future). More accurate waveforms translate into a more accurate determination of the astrophysical parameters of the binary black hole system. Something that hasn't been explored yet is to what extent the self-force analytic approximation, based on an expansion of the gravitational field in integer powers of the extreme mass ratio, generates accurate waveforms as we move towards the less adiabatic phases of the inspiral (for example, closer to the merger of the black holes, in the so called transition region). Understanding the limitations of this methods is necessary if we want to construct waveforms that can accurately describe the adiabatic inspiral, transition and plunge phases of the binary. Evidence has shown that the self-force approximation works well even for intermediate mass ratios (when comparing with NR simulations) during the early inspiral, but this agreement starts to fail as the black holes separation approaches the innermost stable circular orbit. Whether we can overcome this discrepancy with a different approximation will be useful to construct more accurate models. I will talk in more detail about this topic and give an update on our progress.
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