Datensatz

Zusammenfassung

Searching for gravitational waves from compact binary coalescences (CBC) is
performed by matched filtering the observed strain data from gravitational-wave
observatories against a discrete set of waveform templates designed to
accurately approximate the expected gravitational-wave signal, and are chosen
to efficiently cover a target search region. The computational cost of matched
filtering scales with both the number of templates required to cover a
parameter space and the in-band duration of the waveform. Both of these factors
increase in difficulty as the current observatories improve in sensitivity,
especially at low frequencies, and may pose challenges for third-generation
observatories. Reducing the cost of matched filtering would make searches of
future detector's data more tractable. In addition, it would be easier to
conduct searches that incorporate the effects of eccentricity, precession or
target light sources (e.g. subsolar). We present a hierarchical scheme based on
a reduced bases method to decrease the computational cost of conducting a
matched-filter based search. Compared to the current methods, we estimate
without any loss in sensitivity, a speedup by a factor of $\sim$ 18 for sources
with signal-to-noise ratio (SNR) of at least $= 6.0$, and a factor of $8$ for
SNR of at least 5. Our method is dominated by linear operations which are
highly parallelizable. Therefore, we implement our algorithm using graphical
processing units (GPUs) and evaluate commercially motivated metrics to
demonstrate the efficiency of GPUs in CBC searches. Our scheme can be extended
to generic CBC searches and allows for efficient matched filtering using GPUs.