Loading...
Please wait, while we are loading the content...
Similar Documents
Optimizing the Zel ’ dovich Approximation
| Content Provider | Semantic Scholar |
|---|---|
| Author | Melott, Adrian L. Pellman, Todd F. Shandarin, Sergei F. |
| Copyright Year | 1993 |
| Abstract | We have recently learned that the Zeldovich approximation can be successfully used for a far wider range of gravitational instability scenarios than formerly proposed; we study here how to extend this range. In previous work (Coles, Melott and Shandarin 1993, hereafter CMS) we studied the accuracy of several analytic approximations to gravitational clustering in the mildly nonlinear regime. We found that what we called the “truncated Zel’dovich approximation” (TZA) was better than any other (except in one case the ordinary Zeldovich approximation) over a wide range from linear to mildly nonlinear (σ ∼ 3) regimes. TZA was specified by setting Fourier amplitudes equal to zero for all wavenumbers greater than knl, where knl marks the transition to the nonlinear regime. Here, we study the crosscorrelation of generalized TZA with a group of n–body simulations for three shapes of window function: sharp k–truncation (as in CMS), a tophat in coordinate space, or a Gaussian. We also study the variation in the crosscorrelation as a function of initial truncation scale within each type. We find that k–truncation, which was so much better than other things tried in CMS, is the worst of these three window shapes. We find that a Gaussian window e /2k G applied to the intial Fourier amplitudes is the best choice. It produces a greatly improved crosscorrelation in all cases we studied. The optimum choice of kG for the Gaussian window is (a somewhat spectrum–dependent) 1 to 1.5 times knl, where knl is defined by (3). Although all three windows produce similar power spectra and density distribution functions after application of the Zeldovich approximation, the agreement of the phases of the Fourier components with the n–body simulation is better for the Gaussian window. We therefore ascribe the success of the best–choice Gaussian window to its superior treatment of phases in the nonlinear regime. We also report on the accuracy of particle positions and velocities produced by TZA. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://cds.cern.ch/record/252866/files/9312044.pdf |
| Alternate Webpage(s) | http://arxiv.org/pdf/astro-ph/9312044v1.pdf |
| Language | English |
| Access Restriction | Open |
| Subject Keyword | ACM/IEEE Supercomputing Conference Approximation Arabic numeral 0 Cluster analysis Coefficient Computation Cross-correlation Emoticon Fast Fourier transform IBM Notes Initial condition Instability Linear system Microsoft Windows National Center for Supercomputing Applications Nephrogenic Systemic Fibrosis Nonlinear system Normal Statistical Distribution Optimizing compiler Protein Truncation Abnormality Simulation Spectral density Window function funding grant statistical cluster |
| Content Type | Text |
| Resource Type | Article |
