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تسجيل مستخدم جديدStudy on the mapping of halo clustering from real space to redshift space
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Yi Zheng
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The mapping of galaxy clustering from real space to redshift space introduces the anisotropic property to the measured galaxy density power spectrum in redshift space, known as the redshift space distortion (RSD) effect. The mapping formula is intrinsically non-linear, which is complicated by the higher order polynomials due to indefinite orders of cross correlations between density and velocity fields, and the Finger--of--God (FoG) effect due to the randomness of the galaxy peculiar velocity field. In previous works, we have verified the robustness of advanced TNS mapping formula in our hybrid RSD model in dark matter case, where the halo bias models are not taken into account for the halo mapping formula in redshift space. Using 100 realizations of halo catalogs in N-body simulations, we find that our halo RSD model with the known halo bias model and the effective FoG function accurately predicts the halo power spectrum measurements, within 1$sim$2% accuracy up to $ksim 0.2h$/Mpc, depending on different halo masses and redshifts.
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The mapping of dark matter clustering from real space to redshift space introduces the anisotropic property to the measured density power spectrum in redshift space, known as the redshift space distortion effect. The mapping formula is intrinsically
non-linear, which is complicated by the higher order polynomials due to indefinite cross correlations between the density and velocity fields, and the Finger-of-God effect due to the randomness of the peculiar velocity field. Whilst the full higher order polynomials remain unknown, the other systematics can be controlled consistently within the same order truncation in the expansion of the mapping formula, as shown in this paper. The systematic due to the unknown non-linear density and velocity fields is removed by separately measuring all terms in the expansion directly using simulations. The uncertainty caused by the velocity randomness is controlled by splitting the FoG term into two pieces, 1) the one-point FoG term being independent of the separation vector between two different points, and 2) the correlated FoG term appearing as an indefinite polynomials which is expanded in the same order as all other perturbative polynomials. Using 100 realizations of simulations, we find that the Gaussian FoG function with only one scale-independent free parameter works quite well, and that our new mapping formulation accurately reproduces the observed 2-dimensional density power spectrum in redshift space at the smallest scales by far, up to $ksim 0.2h$Mpc, considering the resolution of future experiments.
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Galaxy formation inside dark matter halos, as well as the halo formation itself, can be affected by large-scale environments. Evaluating the imprints of environmental effects on galaxy clustering is crucial for precise cosmological constraints with d
ata from galaxy redshift surveys. We investigate such an environmental impact on both real-space and redshift-space galaxy clustering statistics using a semi-analytic model derived from the Millennium Simulation. We compare clustering statistics from original SAM galaxy samples and shuffled ones with environmental influence on galaxy properties eliminated. Among the luminosity-threshold samples examined, the one with the lowest threshold luminosity (~0.2L_*) is affected by environmental effects the most, which has a ~10% decrease in the real-space two-point correlation function (2PCF) after shuffling. By decomposing the 2PCF into five different components based on the source of pairs, we show that the change in the 2PCF can be explained by the age and richness dependence of halo clustering. The 2PCFs in redshift space are found to change in a similar manner after shuffling. If the environmental effects are neglected, halo occupation distribution modeling of the real-space and redshift-space clustering may have a less than 6.5% systematic uncertainty in constraining beta from the most affected SAM sample and have substantially smaller uncertainties from the other, more luminous samples. We argue that the effect could be even smaller in reality. In the Appendix, we present a method to decompose the 2PCF, which can be applied to measure the two-point auto-correlation functions of galaxy sub-samples in a volume-limited galaxy sample and their two-point cross-correlation functions in a single run utilizing only one random catalog.
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Interacting dark energy models have been proposed as attractive alternatives to $Lambda$CDM. Forthcoming Stage-IV galaxy clustering surveys will constrain these models, but they require accurate modelling of the galaxy power spectrum multipoles on mi
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