The shape of non-Gaussianities

Astronomy and Astrophysics – Astrophysics

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

18 pages, 5 figures

Scientific paper

10.1088/1475-7516/2004/08/009

We study the dependence on configuration in momentum space of the primordial 3-point function of density perturbations in several different scenarios: standard slow-roll inflation, curvaton and variable decay models, ghost inflation, models with higher derivative operators and the DBI model of inflation. We define a cosine between the distributions using a measure based on the ability of experiments to distinguish between them. We find that models fall into two broad categories with fairly orthogonal distributions. Models where non-Gaussianity is created at horizon-crossing during inflation and models in which the evolution outside the horizon dominates. In the first case the 3-point function is largest for equilateral triangles, while in the second the dominant contribution to the signal comes from the influence of long wavelength modes on small wavelength ones. We show that, because the distributions in these two cases are so different, translating constraints on parameters of one model to those of another based on the normalization of the 3-point function for equilateral triangles can be very misleading.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

The shape of non-Gaussianities does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with The shape of non-Gaussianities, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and The shape of non-Gaussianities will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-254136

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.