Machine learning to extract gravitatonal wave transients
Identifying gravitational wave transients, where the waveform cannot be modelled, is complicated because detector data is full of noise transients.
Cutting-edge classification techniques will allow an improved method to distinguish signals from the noise background, increasing the likelihood of making the first detection of a poorly-modelled gravitational-wave transient signal from an event such as a supernova.
Supervisor: Professor Patrick Sutton
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