Testing Higher-Order Lagrangian Perturbation Theory Against Numerical Simulations - 1. Pancake Models

Details Testing Higher-Order Lagrangian Perturbation Theory Against Numerical Simulations - 1. Pancake Models Testing Higher-Order Lagrangian Perturbation Theory Against Numerical Simulations - 1. Pancake Models

1993-09-30

arxiv.org/abs/astro-ph/9309056v1

Astron.Astrophys. 288 (1994) 349-364

Astronomy and Astrophysics

Astrophysics

TeX, 18 pages excl.figures; contact TOB@ibma.ipp-garching.mpg.de ; MELOTT@kusmos.phsx.ukans.edu . submitted to Astron. & Astro

Scientific paper

We present results showing an improvement of the accuracy of perturbation theory as applied to cosmological structure formation for a useful range of quasilinear scales. The Lagrangian theory of gravitational instability of an Einstein-de Sitter dust cosmogony investigated and solved up to the third order in the series of papers by Buchert (1989, 1992, 1993a), Buchert \& Ehlers (1993), Buchert (1993b), Ehlers \& Buchert (1993), is compared with numerical simulations. In this paper we study the dynamics of pancake models as a first step. In previous work (Coles \etal 1993, Melott \etal 1993, Melott 1993) the accuracy of several analytical approximations for the modeling of large-scale structure in the mildly non-linear regime was analyzed in the same way, allowing for direct comparison of the accuracy of various approximations. In particular, the ``Zel'dovich approximation'' (Zel'dovich 1970, 1973, hereafter ZA) as a subclass of the first-order Lagrangian perturbation solutions was found to provide an excellent approximation to the density field in the mildly non-linear regime (i.e. up to a linear r.m.s. density contrast of $\sigma \approx 2$). The performance of ZA in hierarchical clustering models can be greatly improved by truncating the initial power spectrum (smoothing the initial data). We here explore whether this approximation can be further improved with higher-order corrections in the displacement mapping from homogeneity. We study a single pancake model (truncated power-spectrum with power-index $n=-1$) using cross-correlation statistics employed in

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