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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.
We present two-point correlation function statistics of the mass and the halos in the chameleon $f(R)$ modified gravity scenario using a series of large volume N-body simulations. Three distinct variations of $f(R)$ are considered (F4, F5 and F6) and compared to a fiducial $Lambda$CDM model in the redshift range $z in [0,1]$. We find that the matter clustering is indistinguishable for all models except for F4, which shows a significantly steeper slope. The ratio of the redshift- to real-space correlation function at scales $> 20 h^{-1} mathrm{Mpc}$ agrees with the linear General Relativity (GR) Kaiser formula for the viable $f(R)$ models considered. We consider three halo populations characterized by spatial abundances comparable to that of luminous red galaxies (LRGs) and galaxy clusters. The redshift-space halo correlation functions of F4 and F5 deviate significantly from $Lambda$CDM at intermediate and high redshift, as the $f(R)$ halo bias is smaller or equal to that of the $Lambda$CDM case. Finally we introduce a new model independent clustering statistic to distinguish $f(R)$ from GR: the relative halo clustering ratio -- $mathcal{R}$. The sampling required to adequately reduce the scatter in $mathcal{R}$ will be available with the advent of the next generation galaxy redshift surveys. This will foster a prospective avenue to obtain largely model-independent cosmological constraints on this class of modified gravity models.
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 data 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.
(abridged) We investigate the signatures left by the cosmic neutrino background on the clustering of matter, CDM+baryons and halos in redshift-space using a set of more than 1000 N-body and hydrodynamical simulations with massless and massive neutrinos. We find that the effect neutrinos induce on the clustering of CDM+baryons in redshift-space on small scales is almost entirely due to the change in $sigma_8$. Neutrinos imprint a characteristic signature in the quadrupole of the matter (CDM+baryons+neutrinos) field on small scales, that can be used to disentangle the effect of $sigma_8$ and $M_ u$. We show that the effect of neutrinos on the clustering of halos is very different, on all scales, to the one induced by $sigma_8$. We find that the effects of neutrinos of the growth rate of CDM+baryons ranges from $sim0.3%$ to $2%$ on scales $kin[0.01, 0.5]~h{rm Mpc}^{-1}$ for neutrinos with masses $M_ u leqslant 0.15$ eV. We compute the bias between the momentum of halos and the momentum of CDM+baryon and find it to be 1 on large scales for all models with massless and massive neutrinos considered. This point towards a velocity bias between halos and total matter on large scales that it is important to account for in order to extract unbiased neutrino information from velocity/momentum surveys such as kSZ observations. We show that baryonic effects can affect the clustering of matter and CDM+baryons in redshift-space by up to a few percent down to $k=0.5~h{rm Mpc}^{-1}$. We find that hydrodynamics and astrophysical processes, as implemented in our simulations, only distort the relative effect that neutrinos induce on the anisotropic clustering of matter, CDM+baryons and halos in redshift-space by less than $1%$. Thus, the effect of neutrinos in the fully non-linear regime can be written as a transfer function with very weak dependence on astrophysics.
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 mildly non-linear scales. In this work we consider a dark scattering model with a simple 1-parameter extension to $w$CDM - adding only $A$, which describes a pure momentum exchange between dark energy and dark matter. We then provide a comprehensive comparison of three approaches of modeling non-linearities, while including the effects of this dark sector coupling. We base our modeling of non-linearities on the two most popular perturbation theory approaches: TNS and EFTofLSS. To test the validity and precision of the modelling, we perform an MCMC analysis using simulated data corresponding to a $Lambda$CDM fiducial cosmology and Stage-IV surveys specifications in two redshift bins, $z=0.5$ and $z=1$. We find the most complex EFTofLSS-based model studied to be better suited at both, describing the mock data up to smaller scales, and extracting the most information. Using this model, we forecast uncertainties on the dark energy equation of state, $w$, and on the interaction parameter, $A$, finding $sigma_w=0.06$ and $sigma_A=1.1$ b/GeV for the analysis at $z=0.5$ and $sigma_w=0.06$ and $sigma_A=2.0$ b/GeV for the analysis at $z=1$. In addition, we show that a false detection of exotic dark energy up to 3$sigma$ would occur should the non-linear modelling be incorrect, demonstrating the importance of the validation stage for accurate interpretation of measurements.
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