The NINJA-2 project: Detecting and characterizing gravitational
  waveforms modelled using numerical binary black hole simulations
  The Numerical INJection Analysis (NINJA) project is a collaborative effort
between members of the numerical relativity and gravitational-wave astrophysics
communities. The purpose of NINJA is to study the ability to detect
gravitational waves emitted from merging binary black holes and recover their
parameters with next-generation gravitational-wave observatories. We report
here on the results of the second NINJA project, NINJA-2, which employs 60
complete binary black hole hybrid waveforms consisting of a numerical portion
modelling the late inspiral, merger, and ringdown stitched to a post-Newtonian
portion modelling the early inspiral. In a "blind injection challenge" similar
to that conducted in recent LIGO and Virgo science runs, we added 7 hybrid
waveforms to two months of data recolored to predictions of Advanced LIGO and
Advanced Virgo sensitivity curves during their first observing runs. The
resulting data was analyzed by gravitational-wave detection algorithms and 6 of
the waveforms were recovered with false alarm rates smaller than 1 in a
thousand years. Parameter estimation algorithms were run on each of these
waveforms to explore the ability to constrain the masses, component angular
momenta and sky position of these waveforms. We also perform a large-scale
monte-carlo study to assess the ability to recover each of the 60 hybrid
waveforms with early Advanced LIGO and Advanced Virgo sensitivity curves. Our
results predict that early Advanced LIGO and Advanced Virgo will have a
volume-weighted average sensitive distance of 300Mpc (1Gpc) for
$10M_{\odot}+10M_{\odot}$ ($50M_{\odot}+50M_{\odot}$) binary black hole
coalescences. We demonstrate that neglecting the component angular momenta in
the waveform models used in matched-filtering will result in a reduction in
sensitivity for systems with large component angular momenta. [Abstract
abridged for ArXiv, full version in PDF]
