An algorithm for the direct reconstruction of the dark matter correlation function from weak lensing and galaxy clustering - Astrophysics > Cosmology and Nongalactic AstrophysicsReportar como inadecuado




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Abstract: The clustering of matter on cosmological scales is an essential probe forstudying the physical origin and composition of our Universe. To date, most ofthe direct studies have focused on shear-shear weak lensing correlations, butit is also possible to extract the dark matter clustering by combininggalaxy-clustering and galaxy-galaxy-lensing measurements. In this study wedevelop a method that can constrain the dark matter correlation function fromgalaxy clustering and galaxy-galaxy-lensing measurements, by focusing on thecorrelation coefficient between the galaxy and matter overdensity fields. Togenerate a mock galaxy catalogue for testing purposes, we use the HaloOccupation Distribution approach applied to a large ensemble of N-bodysimulations to model pre-existing SDSS Luminous Red Galaxy sample observations.Using this mock catalogue, we show that a direct comparison between the excesssurface mass density measured by lensing and its corresponding galaxyclustering quantity is not optimal. We develop a new statistic that suppressesthe small-scale contributions to these observations and show that this newstatistic leads to a cross-correlation coefficient that is within a few percentof unity down to 5 Mpc-h. Furthermore, the residual incoherence between thegalaxy and matter fields can be explained using a theoretical model forscale-dependent bias, giving us a final estimator that is unbiased to within1%. We also perform a comprehensive study of other physical effects that canaffect the analysis, such as redshift space distortions and differences inradial windows between galaxy clustering and weak lensing observations. Weapply the method to a range of cosmological models and show the viability ofour new statistic to distinguish between cosmological models.



Autor: Tobias Baldauf, Robert E. Smith, Uros Seljak, Rachel Mandelbaum

Fuente: https://arxiv.org/







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