Precision Gravity: black holes, spins and gravitational waves


One of the fundamental questions in modern astrophysics concerns the formation and distribution of compact binaries formed when massive stars collapse to form either neutron stars or black holes. Black hole binaries are believed to be electromagnetically dark, but the recent detections of gravitational waves (GW) from colliding black holes by the advanced laser interferometer gravitational wave observatory (aLIGO) has opened a new window into studying the properties and the origin of compact binaries in the Universe. The measurement of their fundamental properties, i.e. their masses and spins, is only possible through GW observations, in which observed data is compared to theoretical waveform models. In order to perform rapid parameter estimation with minimum bias and perform precision tests of General Relativity, one requires highly accurate and computationally efficient waveform models of precessing binary black holes. This will be increasingly important in forthcoming years as the sensitivity of current and future GW detectors will increase, meaning that the accuracy of waveform models will become increasingly important. The research program proposed here will combine state-of-the-art results in the theoretical modelling of gravitational-wave sources with modern data science methods in order to enable precision measurements of compact binaries. With these results we can accurately determine the astrophysical origin of compact binary parameters, map out their distribution in the Universe and place the tightest constraints on General Relativity in a previously unobserved regime. Concretely, the scientific objectives are:
1. The development of an accurate model of the precession dynamics,
2. The correct incorporation of the equal mass limit,
3. The vetting and validation of this new waveform model against independent waveforms such as from Numerical Relativity,
4. The implementation of this new model in the publicly available LIGO Algorithms Library to be deployed for future GW event analyses to perform parameter inference.


Project number


Main applicant

Dr. P. Schmidt

Affiliated with

Radboud Universiteit Nijmegen

Team members

Dr. P. Schmidt