Description |
The advanced LIGO and Virgo detectors have already observed several tens of gravitational wave signals from the coalescence of compact binary sources comprising of neutron stars and black holes. An accurate reconstruction or estimation of the parameters of these sources is challenging. However, several groups have proposed fast-PE algorithms (both classical and machine learning based) that can solve this inverse problem at a small fraction of the computational cost required in a brute-force approach. In this talk, I will review a few of these algorithms and explain why it is crucial to develop such algorithms from the point of multi-messenger astronomy. I will also introduce a new fast-PE algorithm based on mesh-free approximations that can solve the three-detector binary neutron star problem in a few minutes using 32 CPU cores. Possible applications in upcoming science runs of the LIGO and Virgo detectors and in future space-based detectors will be highlighted.
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