Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userImproving parametric mass modelling of lensing clusters through a perturbative approach
115
0
0.0
(
0
)
Added by
Benjamin Beauchesne
Publication date
2021
fields
Physics
and research's language is
English
Authors
Benjamin Beauchesne
Ask ChatGPT about the research
No Arabic abstract
We present a new method to model the mass distribution of galaxy clusters that combines a parametric and a free-form approach to reconstruct cluster cores with strong lensing constraints. It aims at combining the advantages of both approaches, by keeping the robustness of the parametric component with an increased flexibility thanks to a free-form surface of B-spline functions. We demonstrate the capabilities of this new approach on the simulated cluster Hera, which has been used to evaluate lensing codes for the analysis of the Frontier Fields clusters. The method leads to better reproduction of the constraints, with an improvement by a factor $sim3-4$ on the root-mean-square error on multiple-image positions, when compared to parametric-only approaches. The resulting models show a better accuracy in the reconstruction of the amplitude of the convergence field while conserving a high fidelity on other lensing observables already well reproduced. We make this method publicly available through its implementation in the Lenstool software.
rate research
Read More
Gravitational lensing has long been considered as a valuable tool to determine the total mass of galaxy clusters. The shear profile as inferred from the statistics of ellipticity of background galaxies allows to probe the cluster intermediate and outer regions thus determining the virial mass estimate. However, the mass sheet degeneracy and the need for a large number of background galaxies motivate the search for alternative tracers which can break the degeneracy among model parameters and hence improve the accuracy of the mass estimate. Lensing flexion, i.e. the third derivative of the lensing potential, has been suggested as a good answer to the above quest since it probes the details of the mass profile. We investigate here whether this is indeed the case considering jointly using weak lensing, magnification and flexion. We use a Fisher matrix analysis to forecast the relative improvement in the mass accuracy for different assumptions on the shear and flexion signal - to - noise (S/N) ratio also varying the cluster mass, redshift, and ellipticity. It turns out that the error on the cluster mass may be reduced up to a factor 2 for reasonable values of the flexion S/N ratio. As a general result, we get that the improvement in mass accuracy is larger for more flattened haloes, but extracting general trends is a difficult because of the many parameters at play. We nevertheless find that flexion is as efficient as magnification to increase the accuracy in both mass and concentration determination.
A new method is presented for modelling the physical properties of galaxy clusters. Our technique moves away from the traditional approach of assuming specific parameterised functional forms for the variation of physical quantities within the cluster, and instead allows for a free-form reconstruction, but one for which the level of complexity is determined automatically by the observational data and may depend on position within the cluster. This is achieved by representing each independent cluster property as some interpolating or approximating function that is specified by a set of control points, or nodes, for which the number of nodes, together with their positions and amplitudes, are allowed to vary and are inferred in a Bayesian manner from the data. We illustrate our nodal approach in the case of a spherical cluster by modelling the electron pressure profile Pe(r) in analyses both of simulated Sunyaev-Zeldovich (SZ) data from the Arcminute MicroKelvin Imager (AMI) and of real AMI observations of the cluster MACS J0744+3927 in the CLASH sample. We demonstrate that one may indeed determine the complexity supported by the data in the reconstructed Pe(r), and that one may constrain two very important quantities in such an analysis: the cluster total volume integrated Comptonisation parameter (Ytot) and the extent of the gas distribution in the cluster (rmax). The approach is also well-suited to detecting clusters in blind SZ surveys.
In light of the tension in cosmological constraints reported by the Planck team between their SZ-selected cluster counts and Cosmic Microwave Background (CMB) temperature anisotropies, we compare the Planck cluster mass estimates with robust, weak-lensing mass measurements from the Weighing the Giants (WtG) project. For the 22 clusters in common between the Planck cosmology sample and WtG, we find an overall mass ratio of $left< M_{Planck}/M_{rm WtG} right> = 0.688 pm 0.072$. Extending the sample to clusters not used in the Planck cosmology analysis yields a consistent value of $left< M_{Planck}/M_{rm WtG} right> = 0.698 pm 0.062$ from 38 clusters in common. Identifying the weak-lensing masses as proxies for the true cluster mass (on average), these ratios are $sim 1.6sigma$ lower than the default mass bias of 0.8 assumed in the Planck cluster analysis. Adopting the WtG weak-lensing-based mass calibration would substantially reduce the tension found between the Planck cluster count cosmology results and those from CMB temperature anisotropies, thereby dispensing of the need for new physics such as uncomfortably large neutrino masses (in the context of the measured Planck temperature anisotropies and other data). We also find modest evidence (at 95 per cent confidence) for a mass dependence of the calibration ratio and discuss its potential origin in light of systematic uncertainties in the temperature calibration of the X-ray measurements used to calibrate the Planck cluster masses. Our results exemplify the critical role that robust absolute mass calibration plays in cluster cosmology, and the invaluable role of accurate weak-lensing mass measurements in this regard.
[Abridged] We present a comparison between weak-lensing (WL) and X-ray mass estimates of a sample of numerically simulated clusters. The sample consists on the 20 most massive objects at redshift z=0.25 and Mvir > 5 x 10^{14} Msun h^{-1}. They were found in a cosmological simulation of volume 1 h^{-3} Gpc^3, evolved in the framework of a WMAP-7 normalized cosmology. Each cluster has been resimulated at higher resolution and with more complex gas physics. We processed it thought Skylens and X-MAS to generate optical and X-ray mock observations along three orthogonal projections. The optical simulations include lensing effects on background sources. Standard observational tools and methods of analysis are used to recover the mass profiles of each cluster projection from the mock catalogues. Given the size of our sample, we could also investigate the dependence of the results on cluster morphology, environment, temperature inhomogeneity, and mass. We confirm previous results showing that WL masses obtained from the fit of the cluster tangential shear profiles with NFW functionals are biased low by ~ 5-10% with a large scatter (~10-25%). We show that scatter could be reduced by optimally selecting clusters either having regular morphology or living in substructure-poor environment. The X-ray masses are biased low by a large amount (~25-35%), evidencing the presence of both non-thermal sources of pressure in the ICM and temperature inhomogeneity, but they show a significantly lower scatter than weak-lensing-derived masses. The X-ray mass bias grows from the inner to the outer regions of the clusters. We find that both biases are weakly correlated with the third-order power ratio, while a stronger correlation exists with the centroid shift. Finally, the X-ray bias is strongly connected with temperature inhomogeneities.
We present a method to estimate the lensing potential from massive galaxy clusters for given observational X-ray data. The concepts developed and applied in this work can easily be combined with other techniques to infer the lensing potential, e.g. weak gravitational lensing or galaxy kinematics, to obtain an overall best fit model for the lensing potential. After elaborating on the physical details and assumptions the method is based on, we explain how the numerical algorithm itself is implemented with a Richardson-Lucy algorithm as a central part. Our reconstruction method is tested on simulated galaxy clusters with a spherically symmetric NFW density profile filled with gas in hydrostatic equilibrium. We describe in detail how these simulated observational data sets are created and how they need to be fed into our algorithm. We test the robustness of the algorithm against small parameter changes and estimate the quality of the reconstructed lensing potentials. As it turns out we achieve a very high degree of accuracy in reconstructing the lensing potential. The statistical errors remain below 2.0% whereas the systematical error does not exceed 1.0%.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
