English

Power Spectrum Analysis of the ESP Galaxy Redshift Survey

Astrophysics 2009-10-31 v3

Abstract

We measure the power spectrum of the galaxy distribution in the ESO Slice Project (ESP) galaxy redshift survey. We develope a technique to describe the survey window function analytically, and then deconvolve it from the measured power spectrum using a variant of the Lucy method. We test the whole deconvolution procedure on ESP mock catalogues drawn from large N-body simulations, and find that it is reliable for recovering the correct amplitude and shape of P(k)P(k) at k>0.065hk> 0.065 h Mpc1^{-1}. In general, the technique is applicable to any survey composed by a collection of circular fields with arbitrary pattern on the sky, as typical of surveys based on fibre spectrographs. The estimated power spectrum has a well-defined power-law shape knk^n with n2.2n\simeq -2.2 for k0.2hk\ge 0.2 h Mpc1^{-1}, and a smooth bend to a flatter shape (n1.6n\simeq -1.6) for smaller kk's. The smallest wavenumber, where a meaningful reconstruction can be performed (k0.06hk\sim 0.06 h Mpc1^{-1}), does not allow us to explore the range of scales where other power spectra seem to show a flattening and hints for a turnover. We also find, by direct comparison of the Fourier transforms, that the estimate of the two-point correlation function ξ(s)\xi(s) is much less sensitive to the effect of a problematic window function as that of the ESP, than the power spectrum. Comparison to other surveys shows an excellent agreement with estimates from blue-selected surveys. In particular, the ESP power spectrum is virtually indistinguishable from that of the Durham-UKST survey over the common range of kk's, an indirect confirmation of the quality of the deconvolution technique applied.

Keywords

Cite

@article{arxiv.astro-ph/0007012,
  title  = {Power Spectrum Analysis of the ESP Galaxy Redshift Survey},
  author = {E. Carretti and C. Bertoni and A. Messina and E. Zucca and L. Guzzo},
  journal= {arXiv preprint arXiv:astro-ph/0007012},
  year   = {2009}
}

Comments

15 pages, 11 postscript figures. Version accepted for publication in MNRAS. Complete description of window function computation, 1 additional figure