## 1. IntroductionLy absorption line forests in QSO spectra come
from intervening absorbers, or clouds, with neutral hydrogen column
densities ranging from about to
cm More importantly, unlike other high redshift objects,
Ly forests do not show significant power in their
two-point correlation functions. Aside from very small scales
km/s, all results drawn from the two-point
correlation function of the Ly absorption lines
have failed to detect clustering (Webb, 1987, Weymann 1993, Hu et al.
1995, Cristiani et al. 1997). The power spectrum of the 1-D spatial
distribution of the Ly absorbers is found to be
flat on scales in velocity space of 600 to
30,000 km s It is known that even though the evolution of the power spectrum
during the quasi-linear regime does not significantly differ from the
linear regime, the density perturbations on different scales will no
longer evolve mutually independently because of the power transfer of
perturbations via mode coupling. For popular models, like the cold
dark matter model, the mode-mode coupling of the quasi-linear
evolution leads to a power transfer from large scales to small ones
(Suto & Sasaki 1991). Numerical studies show that the power
transfer is already significant on scales of about
50 h This theory is supported by works based on methods other than the two-point correlation function. For instance, the distribution of nearest neighbor Ly line intervals is found to be definitely different from a Poisson process (Duncan, Ostriker, & Bajtlik 1989; Liu and Jones 1990). A study using the Kolmogorov-Smirnoff (K-S) statistics, finds that Ly absorbers show a deviation from a uniform random distribution at the significance level (Fang, 1991). Some observations also indicate the existence of Mpc void (Dobrzycki & Bechtold 1991), and deviation from uniform distribution on larger scales (Crotts 1987, 1989.) However, this individual structure cannot be used for a statistical analysis. Using a method based on cluster identification, many structures have been systematically identified and formed into an ensemble. It is found that the abundance of the identified "clusters" with respect to the richness are significantly different from a Gaussian process (Pando & Fang 1996, hereafter PF). Recently, we have also found that the Ly forest line distribution shows significant scale-scale correlations. As a consequence models which predict a Gaussian process for the evolution of the Ly clouds are ruled out, and the halos hosting the clouds must have gone through a "history" dependent merging process during their formation (Pando et al. 1998.) In this paper, we will continue to develop the description of the non-Gaussianity of the Ly line distribution. The emphasis of this paper will be to detect the non-Gaussian spectrum, and to show its ability to discriminate among models of Ly cloud formation which are degenerate at second order. In Sect. 2, we will describe the observed and simulated samples of Ly forests, and the problems related to their large scale structure detection. In Sect. 3, the DWT technique of non-Gaussian spectrum detection will be discussed. The results of this analysis for real and simulated samples are discussed in Sect. 4. We will show that the distributions of Ly forest lines are significantly different from Gaussian distributions. Additionally, we show that the non-Gaussian spectrum is a powerful tool for distinguishing between models. © European Southern Observatory (ESO) 1998 Online publication: November 9, 1998 |