Volume 85, Number 2, January 2009
|Number of page(s)||6|
|Section||Geophysics, Astronomy and Astrophysics|
|Published online||02 February 2009|
Persistent fluctuations in the distribution of galaxies from the Two-degree Field Galaxy Redshift Survey
Museo Storico della Fisica e Centro Studi e Ricerche Enrico Fermi - Piazzale del Viminale 1, 00184 Rome, Italy, EU
2 Istituto dei Sistemi Complessi CNR - Via dei Taurini 19, 00185 Rome, Italy, EU
3 Institute of Astronomy, St. Petersburg State University - Staryj Peterhoff, 198504, St. Petersburg, Russia
Corresponding author: Francesco.SylosLabini@roma1.infn.it
Accepted: 17 December 2008
We apply the scale-length method to several three-dimensional samples of the Two-degree Field Galaxy Redshift Survey. This method allows us to map in a quantitative and powerful way large scale structures in the distribution of galaxies controlling systematic effects. By determining the probability density function of conditional fluctuations we show that large-scale structures are quite typical and correspond to large fluctuations in the galaxy density field. We do not find a convergence to homogeneity up to the samples sizes, i.e.≈ 75 Mpc/h. We then measure, at scales r ≲ 40 Mpc/h, a well-defined and statistically stable power law behavior of the average number of galaxies in spheres, with fractal dimension D = 2.2 ± 0.2. We point out that standard models of structure formation are unable to explain the existence of the large fluctuations in the galaxy density field detected in these samples. This conclusion is reached in two ways: by considering the scale, determined by the linear perturbation analysis of a self-gravitating fluid, below which large fluctuations are expected in standard models and through the determination of statistical properties of mock galaxy catalogs generated from cosmological N-body simulations of the Millenium consortitum.
PACS: 98.80.-k – Cosmology / 05.40.-a – Fluctuation phenomena, random processes, noise, and Brownian motion / 02.50.-r – Probability theory, stochastic processes, and statistics
© EPLA, 2009
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