Non Linear Gravitational Clustering in Scale Free Cosmological Models

Non Linear Gravitational Clustering in Scale Free Cosmological Models
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Total Pages : 168
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ISBN-10 : OCLC:882564163
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Book Synopsis Non Linear Gravitational Clustering in Scale Free Cosmological Models by : David Benhaiem

Download or read book Non Linear Gravitational Clustering in Scale Free Cosmological Models written by David Benhaiem and published by . This book was released on 2013 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: The formation of structures in the universe is one of the major questions in cosmology, and numerical N body simulations are the primary instrument used to probe the non linear clustering. However, analytical understanding of this regime remains limited. To explore this regime we study a family of Einstein de Sitter models with cold power law initial conditions. In practice, this means that we have two control parameters on which we can study the dependance of simple crucial analytical predictions for these models : self similarity of the clustering, and the correlation exponents when this clustering is stable. We study first an analogous one dimensional class of models, and find that the stable clustering predictions provide an excellent approximation in the non linear regime for most of the parameter space, while a region in which clustering appears to be universal is observed close to the static limit. We then study N body simulations of the three dimensional models. We find, in the part of the parameter space we can constrain well numerically, that the exponents of the self-similar two point correlation function in the strongly non-linear regime are in excellent agreement with those predicted by stable clustering. Furthermore, preliminary results on the halos extracted from our simulations indicate that the mass profiles of these non-linear structures are well described, as a power law with exponents clearly dependent on the initial conditions and the cosmology, and specifically, correlated with the stable clustering exponents.


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