Full-GR simulations find that inhomogeneous curvature produces only sub-dominant systematic offsets in growth-rate measurements from magnitude fluctuations at z ≲ 0.2 relative to current statistical errors.
A structure in the early universe at z ~ 1.3 that exceeds the homogeneity scale of the R-W concordance cosmology
2 Pith papers cite this work, alongside 150 external citations. Polarity classification is still indexing.
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abstract
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.
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A giant ring structure at z~0.8 is identified with >4σ elliptical shell matches and 3.5σ clustering on ~320 Mpc scales using FilFinder and 2D power spectrum analysis.
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Impact of inhomogeneous curvature on growth rate measurements from magnitude fluctuations
Full-GR simulations find that inhomogeneous curvature produces only sub-dominant systematic offsets in growth-rate measurements from magnitude fluctuations at z ≲ 0.2 relative to current statistical errors.
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A Giant Ring on the sky
A giant ring structure at z~0.8 is identified with >4σ elliptical shell matches and 3.5σ clustering on ~320 Mpc scales using FilFinder and 2D power spectrum analysis.