MG13 - Talk detail

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The Advanced LIGO/Virgo gravitational wave detectors that are currently under construction are poised to give us our first direct detections after commissioning, starting in 2015. Among the most promising sources are coalescences of binary neutron stars and black holes, which are ideal laboratories for studying the strong field dynamics of spacetime. We present TIGER, a Bayesian inference framework which tests the consistency of coefficients appearing in the gravitational waveforms with the predictions made by general relativity (GR), without relying on any specific alternative theory of gravity. TIGER is suitable for low signal-to-noise ratio events through the construction of multiple sub-tests, most of which involve only a limited number of coefficients. It also naturally allows for the combination of information from multiple sources to increase one’s confidence in GR or a violation thereof. In the case of inspiraling binary neutron stars, the method has been fully implemented as a data analysis pipeline. We show results for a range of numerical experiments in simulated stationary and Gaussian noise that follows the expected Advanced LIGO and Virgo noise curves. Potential concerns are addressed, such as differences between waveform approximants, the effects of instrumental calibration errors, tidal deformability of the neutron stars, and the influence of spins. Finally, we discuss possible ways of extending the method to the coalescence of binary black holes.

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