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Genus statistics using the Delaunay tessellation field estimation method: (I) tests with the Millennium Simulation and the SDSS DR7

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arxiv 1006.3768 v2 pith:H4VS6UQV submitted 2010-06-18 astro-ph.CO astro-ph.GA

classification astro-ph.COastro-ph.GA
keywords galaxygenusstatisticsapproachdatafieldmethodsdss
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We study the topology of cosmic large-scale structure through the genus statistics, using galaxy catalogues generated from the Millennium Simulation and observational data from the latest Sloan Digital Sky Survey Data Release (SDSS DR7). We introduce a new method for constructing galaxy density fields and for measuring the genus statistics of its isodensity surfaces. It is based on a Delaunay tessellation field estimation (DTFE) technique that allows the definition of a piece-wise continuous density field and the exact computation of the topology of its polygonal isodensity contours, without introducing any free numerical parameter. Besides this new approach, we also employ the traditional approaches of smoothing the galaxy distribution with a Gaussian of fixed width, or by adaptively smoothing with a kernel that encloses a constant number of neighboring galaxies. Our results show that the Delaunay-based method extracts the largest amount of topological information. Unlike the traditional approach for genus statistics, it is able to discriminate between the different theoretical galaxy catalogues analyzed here, both in real space and in redshift space, even though they are based on the same underlying simulation model. In particular, the DTFE approach detects with high confidence a discrepancy of one of the semi-analytic models studied here compared with the SDSS data, while the other models are found to be consistent.

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  1. Cosmological constraints from the Minkowski functionals of the BOSS CMASS galaxy sample

    astro-ph.CO 2025-01 conditional novelty 6.0 of 10

    A simulation-based emulator of Minkowski functionals applied to BOSS CMASS galaxies yields cosmological constraints from both Gaussian and non-Gaussian information, tighter than the 2PCF alone.

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