Journal Article

The non-linear probability distribution function in models with local primordial non-Gaussianity

Tsz Yan Lam and Ravi K. Sheth

in Monthly Notices of the Royal Astronomical Society

Published on behalf of The Royal Astronomical Society

Volume 395, issue 3, pages 1743-1748
Published in print May 2009 | ISSN: 0035-8711
Published online May 2009 | e-ISSN: 1365-2966 | DOI: http://dx.doi.org/10.1111/j.1365-2966.2009.14672.x
The non-linear probability distribution function in models with local primordial non-Gaussianity

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We use the spherical evolution approximation to investigate non-linear evolution from the non-Gaussian initial conditions characteristic of the local fnl model. We provide an analytic formula for the non-linearly evolved probability distribution function (PDF) of the dark matter which shows that the underdense tail of the non-linear PDF in the fnl model should differ significantly from that for Gaussian initial conditions. Measurements of the underdense tail in numerical simulations may be affected by discreteness effects, and we use a Poisson counting model to describe this effect. Once this has been accounted, our model is in good quantitative agreement with the simulations. In principle, our calculation is an important first step in programs which seek to reconstruct the shape of the initial PDF from observations of large-scale structures in the Lyα forest and the galaxy distribution at later times.

Keywords: methods: analytical; dark matter; large scale structure of Universe

Journal Article.  3465 words.  Illustrated.

Subjects: Astronomy and Astrophysics

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