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A Large Quasar Group (LQG) of particularly large size and high membership has been identified in the DR7QSO catalogue of the Sloan Digital Sky Survey. It has characteristic size (volume^1/3) ~ 500 Mpc (proper size, present epoch), longest dimension ~ 1240 Mpc, membership of 73 quasars, and mean redshift <z> = 1.27. In terms of both size and membership it is the most extreme LQG found in the DR7QSO catalogue for the redshift range 1.0 <= z <= 1.8 of our current investigation. Its location on the sky is ~ 8.8 deg north (~ 615 Mpc projected) of the Clowes & Campusano LQG at the same redshift, <z> = 1.28, which is itself one of the more extreme examples. Their boundaries approach to within ~ 2 deg (~ 140 Mpc projected). This new, huge LQG appears to be the largest structure currently known in the early universe. Its size suggests incompatibility with the Yadav et al. scale of homogeneity for the concordance cosmology, and thus challenges the assumption of the cosmological principle.
We use the scaled counts in spherical caps $mathcal{N}(<theta)$ and the fractal correlation dimension $ mathcal{D}_{2}(theta) $ procedures to search for a transition scale to homogeneity in the local universe as given by the ALFALFA catalogue (a samp
We confirm the detection of 3 groups in the Lynx supercluster, at z~1.3, and give their redshifts and masses. We study the properties of the group galaxies as compared to the central clusters, RXJ0849+4452 and RXJ0848+4453, selecting 89 galaxies in t
We probe the angular scale of homogeneity in the local Universe using blue galaxies from the SDSS survey as a cosmological tracer. Through the scaled counts in spherical caps, $ mathcal{N}(<theta) $, and the fractal correlation dimension, $mathcal{D}
We present and test a framework that models the three-dimensional distribution of mass in the Universe as a function of cosmological and astrophysical parameters. Our approach combines two different techniques: a rescaling algorithm that modifies the
We propose a new intuitive metric for evaluating the tension between two experiments, and apply it to several data sets. While our metric is non-optimal, if evidence of tension is detected, this evidence is robust and easy to interpret. Assuming a fl