Cosmological Constraints from applying SHAM to rescaled cosmological simulations

Abstract

We place constraints on the matter density of the Universe and the amplitude of clustering using measurements of the galaxy two-point correlation function from the Sloan Digital Sky Survey (SDSS). We generate model predictions for different cosmologies by populating rescaled N-body simulations with galaxies using the subhalo abundance matching (SHAM) technique. We find Omega-M = 0.29 +/- 0.03 and sigma-8 = 0.86 +/- 0.04 at 68% confidence from fitting the observed two-point galaxy correlation function of galaxies brighter than M_r = -18 in a volume limited sample of galaxies obtained by the SDSS. We discuss and quantify potential sources of systematic error, and conclude that while there is scope for improving its robustness, the technique presented in this paper provides a powerful low redshift constraint on the cosmological parameters that is complementary to other commonly used methods.

10 pages, 11 figures, submitted to MNRAS

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• Rapid simulation rescaling from standard to modified gravity models
• Small-scale galaxy clustering in the EAGLE simulation
• The MillenniumTNG Project: Inferring cosmology from galaxy clustering with accelerated N-body scaling and subhalo abundance matching
• Remapping dark matter halo catalogues between cosmological simulations
• Simulating the Anisotropic Clustering of Luminous Red Galaxies with Subhalos: A Direct Confrontation with Observation and Cosmological Implications
• Remapping simulated halo catalogues in redshift space
• Measuring the growth of structure by matching dark matter haloes to galaxies with VIPERS and SDSS
• Inferring Cosmological Parameters on SDSS via Domain-Generalized Neural Networks and Lightcone Simulations
• Observations of General Relativity at strong and weak limits