We present a novel gravitational wave detection algorithm that conducts a
    matched filter search stochastically across the compact binary parameter space
    rather than relying on a fixed bank of template waveforms. This technique is
    competitive with standard template-bank-driven pipelines in both computational
    cost and sensitivity. However, the complexity of the analysis is simpler
    allowing for easy configuration and horizontal scaling across heterogeneous
    grids of computers. To demonstrate the method we analyze approximately one
    month of public LIGO data from July 27 00:00 2017 UTC – Aug 25 22:00 2017 UTC
    and recover eight known confident gravitational wave candidates. We also inject
    simulated binary black hole (BBH) signals to demonstrate the sensitivity.

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