67 citations · 275 across the 8 of their papers we have counts for
8 papers
Characterizing the large scale inhomogeneity of the galaxy distribution
Francesco Sylos Labini
In order to investigate whether galaxy structures are compatible with the predictions of the standard LCDM cosmology, we focus here on the analysis of several simple and basic stat…
Breaking the self-averaging properties of spatial galaxy fluctuations in the Sloan Digital Sky Survey - Data Release Six
Francesco Sylos Labini, Nikolay L. Vasilyev, Yurij V. Baryshev
Statistical analyses of finite sample distributions usually assume that fluctuations are self-averaging, i.e. that they are statistically similar in different regions of the given…
Galaxy distribution and extreme value statistics
Tibor Antal, Francesco Sylos Labini, Nikolay L. Vasilyev +1
We consider the conditional galaxy density around each galaxy, and study its fluctuations in the newest samples of the Sloan Digital Sky Survey Data Release 7. Over a large range o…
Absence of anti-correlations and of baryon acoustic oscillations in the galaxy correlation function from the Sloan Digital Sky Survey DR7
Francesco Sylos Labini, Nikolay L. Vasilyev, Yurij V. Baryshev +1
One of the most striking features predicted by standard models of galaxy formation is the presence of anti-correlations in the matter distribution at large enough scales (r>r_c). S…
Large-scale fluctuations in the distribution of galaxies from the Two Degree Field Galaxy Redshift Survey
Francesco Sylos Labini, Nikolay L. Vasilyev, Yurij V. Baryshev
We study statistical properties of galaxy structures in several samples extracted from the 2dF Galaxy Redshift Survey. In particular, we measured conditional fluctuations by means…
Persistent fluctuations in the distribution of galaxies from the Two degree Field Galaxy Redshift Survey
Francesco Sylos Labini, Nikolay L. Vasilyev, Yurij V. Baryshev
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 wa…