Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userEnvironmental Effects on Real-Space and Redshift-Space Galaxy Clustering
184
0
0.0
(
0
)
Ask ChatGPT about the research
No Arabic abstract
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.
rate research
Read More
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.
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.
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.
Observations of galaxy clustering are made in redshift space, which results in distortions to the underlying isotropic distribution of galaxies. These redshift-space distortions (RSD) not only degrade important features of the matter density field, such as the baryonic acoustic oscillation (BAO) peaks, but also pose challenges for the theoretical modelling of observational probes. Here we introduce an iterative nonlinear reconstruction algorithm to remove RSD effects from galaxy clustering measurements, and assess its performance by using mock galaxy catalogues. The new method is found to be able to recover the real-space galaxy correlation function with an accuracy of $sim1%$, and restore the quadrupole accurately to $0$, on scales $sgtrsim20Mpch$. It also leads to an improvement in the reconstruction of the initial density field, which could help to accurately locate the BAO peaks. An `internal calibration scheme is proposed to determine the values of cosmological parameters as a part of the reconstruction process, and possibilities to break parameter degeneracies are discussed. RSD reconstruction can offer a potential way to simultaneously extract the cosmological parameters, initial density field, real-space galaxy positions and large-scale peculiar velocity field (of the real Universe), making it an alternative to standard perturbative approaches in galaxy clustering analysis, bypassing the need for RSD modelling.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
