We have studied the galaxygroup crosscorrelations in redshift space for the Galaxy And Mass Assembly (GAMA) Survey. We use a set of mock GAMA galaxy and group catalogues to develop and test a novel ‘halo streaming’ model for redshiftspace distortions. This treats 2halo correlations via the streaming model, plus an empirical 1halo term derived from the mocks, allowing accurate modelling into the nonlinear regime. In order to probe the robustness of the growth rate inferred from redshiftspace distortions, we divide galaxies by colour, and divide groups according to their total stellar mass, calibrated to total mass via gravitational lensing. We fit our model to correlation data, to obtain estimates of the perturbation growth rate, fσ8, validating parameter errors via the dispersion between different mock realizations. In both mocks and real data, we demonstrate that the results are closely consistent between different subsets of the group and galaxy populations, considering the use of correlation data down to some minimum projected radius, rmin. For the mock data, we can use the halo streaming model to below $r_{\rm min} = 5{\, h^{1}\, \rm Mpc}$, finding that all subsets yield growth rates within about 3 per cent of each other, and consistent with the true value. For the actual GAMA data, the results are limited by cosmic variance: fσ8 = 0.29 ± 0.10 at an effective redshift of 0.20; but there is every reason to expect that this method will yield precise constraints from larger data sets of the same type, such as the Dark Energy Spectroscopic Instrument (DESI) bright galaxy survey.
 Award ID(s):
 1713791
 NSFPAR ID:
 10093430
 Date Published:
 Journal Name:
 Journal of cosmology and astroparticle physics
 Volume:
 03
 ISSN:
 14757516
 Page Range / eLocation ID:
 007
 Format(s):
 Medium: X
 Sponsoring Org:
 National Science Foundation
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