اشترك بالحزمة الذهبية واحصل على وصول غير محدود شمرا أكاديميا
تسجيل مستخدم جديدLinear and nonlinear contributions to pairwise peculiar velocities
60
0
0.0
(
0
)
تأليف
Ravi K. Sheth
اسأل ChatGPT حول البحث
ﻻ يوجد ملخص باللغة العربية
We write the correlation function of dark matter particles, xi(r), as the sum of two terms - one which accounts for nonlinear evolution, and dominates on small scales, and another which is essentially the term from linear theory, and dominates on large scales. We use models of the number and spatial distribution of haloes and halo density profiles to describe the nonlinear term and its evolution. The result provides a good description of the evolution of xi(r) in simulations. We then use this decomposition to provide simple and accurate models of how the single particle velocity dispersion evolves with time, and how the first and second moments of the pairwise velocity distribution depend on scale. The key idea is to use the simple physics of linear theory on large scales, the simple physics of the virial theorem on small scales, and our model for the correlation function to tell us how to weight the two types of contributions (linear and nonlinear) to the pairwise velocity statistics. When incorporated into the streaming model, our results will allow a simple accurate description of redshift-space distortions over the entire range of linear to highly nonlinear regimes.
قيم البحث
اقرأ أيضاً
We allow for nonlinear effects in the likelihood analysis of galaxy peculiar velocities, and obtain ~35%-lower values for the cosmological density parameter Om and the amplitude of mass-density fluctuations. The power spectrum in the linear regime is
assumed to be a flat LCDM model (h=0.65, n=1, COBE) with only Om as a free parameter. Since the likelihood is driven by the nonlinear regime, we break the power spectrum at k_b=0.2 h/Mpc and fit a power law at k>k_b. This allows for independent matching of the nonlinear behavior and an unbiased fit in the linear regime. The analysis assumes Gaussian fluctuations and errors, and a linear relation between velocity and density. Tests using proper mock catalogs demonstrate a reduced bias and a better fit. We find for the Mark3 and SFI data Om_m=0.32+-0.06 and 0.37+-0.09 respectively, with sigma_8*Om^0.6 = 0.49+-0.06 and 0.63+-0.08, in agreement with constraints from other data. The quoted 90% errors include cosmic variance. The improvement in likelihood due to the nonlinear correction is very significant for Mark3 and moderately so for SFI. When allowing deviations from LCDM, we find an indication for a wiggle in the power spectrum: an excess near k=0.05 and a deficiency at k=0.1 (cold flow). This may be related to the wiggle seen in the power spectrum from redshift surveys and the second peak in the CMB anisotropy. A chi^2 test applied to modes of a Principal Component Analysis (PCA) shows that the nonlinear procedure improves the goodness of fit and reduces a spatial gradient of concern in the linear analysis. The PCA allows addressing spatial features of the data and fine-tuning the theoretical and error models. It shows that the models used are appropriate for the cosmological parameter estimation performed. We address the potential for optimal data compression using PCA.
We investigate peculiar velocities predicted for clusters in Lambda cold dark matter ($Lambda$CDM) models assuming that the initial density fluctuation field is Gaussian. To study the non-linear regime, we use N-body simulations. We investigate the r
ms velocity and the probability distribution function of cluster peculiar velocities for different cluster masses. To identify clusters in the simulation we use two methods: the standard friends-of-friends (FOF) method and the method, where the clusters are defined as maxima of a smoothed density field (DMAX). The density field is smoothed with a top-hat window, using the smoothing radii $R_s=1.5h^{-1}$ Mpc and $R_s=1.0h^{-1}$ Mpc. The peculiar velocity of the DMAX clusters is defined to be the mean peculiar velocity of matter within a sphere of the radius $R_s$. We find that the rms velocity of the FOF clusters decreases as the cluster mass increases. The rms velocity of the DMAX clusters is almost independent of the cluster mass and is well approximated by the linear rms peculiar velocity smoothed at the radius $R=R_s$. The velocity distribution function of the DMAX clusters is similar to a Gaussian.
Surveys of galaxy distances and radial peculiar velocities can be used to reconstruct the large scale structure. Other than systematic errors in the zero-point calibration of the galaxy distances the main source of uncertainties of such data are erro
rs on the distance moduli, assumed here to be Gaussian and thus turn into lognormal errors on distances and velocities. Naively treated, it leads to spurious nearby outflow and strong infall at larger distances. The lognormal bias is corrected here and tested against mock data extracted from a $Lambda$CDM simulation, designed to statistically follow the grouped Cosmicflows-3 (CF3) data. Considering a subsample of data points, all of which have the same true distances or same redshifts, the lognormal bias arises because the means of the distributions of observed distances and velocities are skewed off the means of the true distances and velocities. Yet, the medians are invariant under the lognormal transformation. That invariance allows the Gaussianization of the distances and velocities and the removal of the lognormal bias. This Bias Gaussianization correction (BGc) algorithm is tested against mock CF3 catalogs. The test consists of a comparison of the BGC estimated with the simulated distances and velocities and of an examination of the Wiener filter reconstruction from the BGc data. Indeed, the BGc eliminates the lognormal bias. The estimation of Hubbles ($H_{0}$) constant is also tested. The residual of the BGc estimated $H_{0}$ from the simulated values is $0.6 pm 0.7 {rm kms}^{-1}{rm Mpc}^{-1}$ and is dominated by the cosmic variance. The BGc correction of the actual CF3 data yields $H_{0} = 75.8 pm 1.1 {rm kms}^{-1}{rm Mpc}^{-1}$ .
We perform statistical analyses to study the infall of galaxies onto groups and clusters in the nearby Universe. The study is based on the UZC and SSRS2 group catalogs and peculiar velocity samples. We find a clear signature of infall of galaxies ont
o groups over a wide range of scales 5 h^{-1} Mpc<r<30 h^{-1} Mpc, with an infall amplitude on the order of a few hundred kilometers per second. We obtain a significant increase in the infall amplitude with group virial mass (M_{V}) and luminosity of group member galaxies (L_{g}). Groups with M_{V}<10^{13} M_{odot} show infall velocities V_{infall} simeq 150 km s^{-1} whereas for M_{V}>10^{13} M_{odot} a larger infall is observed, V_{infall} simeq 200 km s^{-1}. Similarly, we find that galaxies surrounding groups with L_{g}<10^{15} L_{odot} have V_{infall} simeq 100 km s^{-1}, whereas for L_{g}>10^{15} L_{odot} groups, the amplitude of the galaxy infall can be as large as V_{infall} simeq 250 km s^{-1}. The observational results are compared with the results obtained from mock group and galaxy samples constructed from numerical simulations, which include galaxy formation through semianalytical models. We obtain a general agreement between the results from the mock catalogs and the observations. The infall of galaxies onto groups is suitably reproduced in the simulations and, as in the observations, larger virial mass and luminosity groups exhibit the largest galaxy infall amplitudes. We derive estimates of the integrated mass overdensities associated with groups by applying linear theory to the infall velocities after correcting for the effects of distance uncertainties obtained using the mock catalogs. The resulting overdensities are consistent with a power law with delta sim 1 at r sim 10 h^{-1}Mpc.
The line-of-sight peculiar velocities of galaxies contribute to their observed redshifts, breaking the translational invariance of galaxy clustering down to a rotational invariance around the observer. This becomes important when the line-of-sight di
rection varies significantly across a survey, leading to what are known as `wide angle effects in redshift space distortions. Wide-angle effects will also be present in measurements of the momentum field, i.e. the galaxy density-weighted velocity field, in upcoming peculiar velocity surveys. In this work we study how wide-angle effects modify the predicted correlation function and power spectrum for momentum statistics, both in auto-correlation and in cross-correlation with the density field. Using both linear theory and the Zeldovich approximation, we find that deviations from the plane-parallel limit are large and could become important in data analysis for low redshift surveys. We point out that even multipoles in the cross-correlation between density and momentum are non-zero regardless of the choice of line of sight, and therefore contain new cosmological information that could be exploited. We discuss configuration-space, Fourier-space and spherical analyses, providing exact expressions in each case rather than relying on an expansion in small angles. We hope these expressions will be of use in the analysis of upcoming surveys for redshift-space distortions and peculiar velocities.
سجل دخول لتتمكن من نشر تعليقات
التعليقات
جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
