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Topology of non-linear structure in the 2dF Galaxy Redshift Survey
We study the evolution of non-linear structure as a function of scale in samples from the 2dF Galaxy Redshift Survey, constituting over 221 000 galaxies at a median redshift of z= 0.11. The two flux-limited galaxy samples, located near the Southern Galactic Pole and the Galactic equator, are smoothe...
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Published in: | Monthly notices of the Royal Astronomical Society 2009-03, Vol.394 (1), p.454-466 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | We study the evolution of non-linear structure as a function of scale in samples from the 2dF Galaxy Redshift Survey, constituting over 221 000 galaxies at a median redshift of z= 0.11. The two flux-limited galaxy samples, located near the Southern Galactic Pole and the Galactic equator, are smoothed with Gaussian filters of width ranging from 5 to 8 h−1 Mpc to produce a continuous galaxy density field. The topological genus statistic is used to measure the relative abundance of overdense clusters to void regions at each scale; these results are compared with the predictions of the analytic theory, in the form of the genus statistic for (i) the linear regime case of a Gaussian random field and (ii) a first-order perturbative expansion of the weakly non-linear evolved field. The measurements demonstrate a statistically significant detection of an asymmetry in the genus statistic between regions corresponding to low- and high-density volumes of the Universe. We attribute the asymmetry to the non-linear effects of the gravitational evolution and biased galaxy formation, and demonstrate that these effects evolve as a function of scale. We find that neither analytic prescription satisfactorily reproduces the measurements, though the weakly non-linear theory yields substantially better results at some scales, and we discuss the potential explanations for this result. |
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ISSN: | 0035-8711 1365-2966 |
DOI: | 10.1111/j.1365-2966.2008.14358.x |