Fast Computation of Bispectrum Features with Generalized Slow Roll
  We develop a fast technique based on the generalized slow roll (GSR) approach
for computing the curvature bispectrum of inflationary models with features. We
show that all triangle configurations can be expressed in terms of three simple
integrals over the inflationary background with typical accuracy of better than
~20%. With a first order GSR approach the typical accuracy can be improved to
better than the 5% level. We illustrate this technique with the step potential
model that has been invoked to explain the WMAP temperature power spectrum
glitches at ell ~ 20-40 and show that the maximum likelihood model falls short
of observability by more than a factor of 100 in amplitude. We also explicitly
demonstrate that the bispectrum consistency relation with the local slope of
the power spectrum is satisfied for these models. In the GSR approach, the
bispectrum arises from integrals of nearly the same function of the background
slow-roll parameters as the power spectrum but with a stronger weight to the
epoch before horizon crossing. Hence this technique enables reverse engineering
of models with large bispectrum but small power spectrum features.
