Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userNew method for initial density reconstruction
73
0
0.0
(
0
)
Authors
Yanlong Shi
Ask ChatGPT about the research
No Arabic abstract
A theoretically interesting and practically important question in cosmology is the reconstruction of the initial density distribution provided a late-time density field. This is a long-standing question with a revived interest recently, especially in the context of optimally extracting the baryonic acoustic oscillation (BAO) signals from observed galaxy distributions. We present a new efficient method to carry out this reconstruction, which is based on numerical solutions to the nonlinear partial differential equation that governs the mapping between the initial Lagrangian and final Eulerian coordinates of particles in evolved density fields. This is motivated by numerical simulations of the quartic Galileon gravity model, which has similar equations that can be solved effectively by multigrid Gauss-Seidel relaxation. The method is based on mass conservation, and does not assume any specific cosmological model. Our test shows that it has a performance comparable to that of state-of-the-art algorithms which were very recently put forward in the literature, with the reconstructed density field over $sim80%$ ($50%$) correlated with the initial condition at $klesssim0.6h/{rm Mpc}$ ($1.0h/{rm Mpc}$). With an example, we demonstrate that this method can significantly improve the accuracy of BAO reconstruction.
rate research
Read More
We present a method for investigating variations in the upper end of the stellar Initial Mass Function (IMF) by probing the production rate of ionizing photons in unresolved, compact star clusters with ages <~10 Myr and with different masses. We test this method by performing a pilot study on the young cluster population in the nearby galaxy NGC5194 (M51a), for which multi-wavelength observations from the Hubble Space Telescope are available. Our results indicate that the proposed method can probe the upper end of the IMF in galaxies located out to at least ~10 Mpc, i.e., a factor ~200 further away than possible by counting individual stars in young compact clusters. Our results for NGC5194 show no obvious dependence of the upper mass end of the IMF on the mass of the star cluster down to ~1000 M_sun, although more extensive analyses involving lower mass clusters and other galaxies are needed to confirm this conclusion.
We develop a maximum likelihood based method of reconstructing band powers of the density and velocity power spectra at each wavenumber bins from the measured clustering features of galaxies in redshift space, including marginalization over uncertainties inherent in the Fingers-of-God (FoG) effect. The reconstruction can be done assuming that the density and velocity power spectra depend on the redshift-space power spectrum having different angular modulations of mu with mu^{2n} (n=0,1,2) and that the model FoG effect is given as a multiplicative function in the redshift-space spectrum. By using N-body simulations and the halo catalogs, we test our method by comparing the reconstructed power spectra with the simulations. For the spectrum of mu^0 or equivalently the density power spectrum P_dd(k), our method recovers the amplitudes to a few percent accuracies up to k=0.3 h/Mpc for both dark matter and halos. For the power spectrum of mu^2, which is equivalent to the density-velocity spectrum P_dv(k) in the linear regime, our method can recover the input power spectrum for dark matter up to k=0.2 h/Mpc and at both z=0 and 1, if using the adequate FoG model. However, for the halo spectrum, the reconstructed spectrum shows greater amplitudes than the simulation P_dv(k). We argue that the disagreement is ascribed to nonlinearity effect that arises from the cross-bispectra of density and velocity perturbations. Using the perturbation theory, we derive the nonlinear correction term, and find that the leading-order correction term is proportional to mu^2 and increases the mu^2-power spectrum amplitudes at larger k, at lower redshifts and for more massive halos. We find that adding the nonlinearity correction term to the simulation P_dv(k) can fairly well reproduce the reconstructed P_dv(k) for halos up to k~0.2 h/Mpc.
We have pioneered a new method for the measurement of extragalactic distances. This method uses the time-lag between variations in the short wavelength and long wavelength light from an active galactic nucleus (AGN), based on a quantitative physical model of dust reverberation that relates the time-lag to the absolute luminosity of the AGN. We use the large homogeneous data set from intensive monitoring observations in optical and near-infrared wavelength bands with the dedicated 2-m MAGNUM telescope to obtain the distances to 17 AGNs in the redshift range z=0.0024 to z=0.0353. These distance measurements are compared with distances measured using Cepheid variable stars, and are used to infer that H_0= 73 +- 3 (random) km/s/Mpc. The systematic error in H_0 is examined, and the uncertainty in the size distribution of dust grains is the largest source of the systematic error, which is much reduced for a sample of AGNs for which their parameter values in the model of dust reverberation are individually measured. This AGN time-lag method can be used beyond 30 Mpc, the farthest distance reached by extragalactic Cepheids, and can be extended to high-redshift quasi-stellar objects.
We present a new method to measure the redshift-dependent galaxy bias by combining information from the galaxy density field and the weak lensing field. This method is based on Amara et al. (2012), where they use the galaxy density field to construct a bias-weighted convergence field kg. The main difference between Amara et al. (2012) and our new implementation is that here we present another way to measure galaxy bias using tomography instead of bias parameterizations. The correlation between kg and the true lensing field k allows us to measure galaxy bias using different zero-lag correlations, such as <kgk>/<kk> or <kgkg>/<kgk>. Our method measures the linear bias factor on linear scales under the assumption of no stochasticity between galaxies and matter. We use the MICE simulation to measure the linear galaxy bias for a flux-limited sample (i < 22.5) in tomographic redshift bins using this method. This paper is the first that studies the accuracy and systematic uncertainties associated with the implementation of the method, and the regime where it is consistent with the linear galaxy bias defined by projected 2-point correlation functions (2PCF). We find that our method is consistent with linear bias at the percent level for scales larger than 30 arcmin, while nonlinearities appear at smaller scales. This measurement is a good complement to other measurements of bias, since it does not depend strongly on sigma8 as the 2PCF measurements. We apply this method to the Dark Energy Survey Science Verification data in a follow-up paper.
Model independent reconstructions of dark energy have received some attention. The approach that addresses the reconstruction of the dimensionless coordinate distance and its two first derivatives using a polynomial fit in different redshift windows is well developed cite{DalyDjorgovski1,DalyDjorgovski2,DalyDjorgovski3}. In this work we offer new insights into the problem by focusing on two types of observational probes: SNeIa and GRBs. Our results allow to highlight some of the intrinsic weaknesses of the method. One of the directions we follow is to consider updated observational samples. Our results indicate than conclusions on the main dark energy features as drawn from this method are intimately related to the features of the samples themselves (which are not quite ideal). This is particularly true of GRBs, which manifest themselves as poor performers in this context. In contrast to original works, we conclude they cannot be used for cosmological purposes, and the state of the art does not allow to regard them on the same quality basis as SNeIa. The next direction we contribute to is the question of how the adjusting of some parameters (window width, overlap, selection criteria) affect the results. We find again there is a considerable sensitivity to these features. Then, we try to establish what is the current redshift range for which one can make solid predictions on dark energy evolution. Finally, we strengthen the former view that this model is modest in the sense it provides only a picture of the global trend. But, on the other hand, we believe it offers an interesting complement to other approaches given that it works on minimal assumptions.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
