Temporal optimization of Lagrangian perturbation schemes

Details Temporal optimization of Lagrangian perturbation schemes Temporal optimization of Lagrangian perturbation schemes

1996-07-30

arxiv.org/abs/astro-ph/9607161v3

Astron.Astrophys.326:873-884,1997

Astronomy and Astrophysics

Astrophysics

Astron. Astrophys., in press; TeX 5 pages incl. Fig.3; this replacement includes all the figures (Figs.1-12)

Scientific paper

The Lagrangian perturbation theory on Friedmann-Lemaitre cosmologies is compared with numerical simulations (tree-, adaptive P$^3$M- and PM codes). In previous work we have probed the large-scale performance of the Lagrangian perturbation solutions up to the third order by studying their cross- correlations with N-body simulations for various power spectra (Buchert etal 1994, Melott etal 1995, Weiss etal 1996). Thereby, spatial optimization techniques were applied by (high-frequency-)filtering of the initial power spectra. In this work the novel method of temporal optimization [Shifted-Time- Approximation (STA) and Frozen-Time-Approximation (FTA)] is investigated and used. The method is designed to compensate the native property of Lagrangian perturbation solutions to delay the collapse of structures. The method can be treated analytically. Applying the STA and FTA prescriptions a significant improvement of the performance of Lagrangian perturbation schemes (as measured by cross-correlation statistics) is observed. Using this tool we investigate a local study of special clustering models of dark matter as candidates for typical elements of the large-scale structure in the Universe, and so also focus on the performance of the perturbation solutions on smaller scales at high-spatial resolution. The models analyzed were presented in (Buchert etal 1996) and allow studying typical features of the clustering process in the weakly non-linear regime. The spatial and temporal limits of applicability of the solutions at second and third order are determined and compared with the first-order solution, which is equivalent to the ``Zel'dovich approximation'' (Zel'dovich 1970, 1973) for the type of initial data analyzed.

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