Gravitational wave science is a pioneering field with rapidly evolving data analysis methodology currently assimilating and inventing deep learning techniques. The bulk of the sophisticated flagship searches rely on time-tested matched filtering principle within their core. In this paper, we make key observation relationship between emerging traditional techniques: formally equivalent to partic...

Searching for gravitational waves from compact binary coalescence (CBC) is performed by matched filtering the observed strain data gravitational-wave observatories against a discrete set of waveform templates designed to accurately approximate expected signal, and are chosen efficiently cover target search region. The computational cost scales with both number required parameter space in-band d...