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Register a new userStrong and weak lensing united I: the combined strong and weak lensing cluster mass reconstruction method
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M. Bradac
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Weak gravitational lensing is considered to be one of the most powerful tools to study the mass and the mass distribution of galaxy clusters. However, the mass-sheet degeneracy transformation has limited its success. We present a novel method for a cluster mass reconstruction which combines weak and strong lensing information on common scales and can, as a consequence, break the mass-sheet degeneracy. We extend the weak lensing formalism to the inner parts of the cluster and combine it with the constraints from multiple image systems. We demonstrate the feasibility of the method with simulations, finding an excellent agreement between the input and reconstructed mass also on scales within and beyond the Einstein radius. Using a single multiple image system and photometric redshift information of the background sources used for weak and strong lensing analysis, we find that we are effectively able to break the mass-sheet degeneracy, therefore removing one of the main limitations on cluster mass estimates. We conclude that with high resolution (e.g. HST) imaging data the method can more accurately reconstruct cluster masses and their profiles than currently existing lensing techniques.
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After a brief introduction to gravitational lensing theory, a rough overview of the types of gravitational lensing statistics that have been performed so far will be given. I shall then concentrate on recent results of galaxy-galaxy lensing, which indicate that galactic halos extend much further than can be probed via rotation of stars and gas.
The galaxy cluster 1E0657-56 (z = 0.296) is remarkably well-suited for addressing outstanding issues in both galaxy evolution and fundamental physics. We present a reconstruction of the mass distribution from both strong and weak gravitational lensing data. Multi-color, high-resolution HST ACS images allow detection of many more arc candidates than were previously known, especially around the subcluster. Using the known redshift of one of the multiply imaged systems, we determine the remaining source redshifts using the predictive power of the strong lens model. Combining this information with shape measurements of weakly lensed sources, we derive a high-resolution, absolutely-calibrated mass map, using no assumptions regarding the physical properties of the underlying cluster potential. This map provides the best available quantification of the total mass of the central part of the cluster. We also confirm the result from Clowe et al. (2004,2006a).
We have shown that the cluster-mass reconstruction method which combines strong and weak gravitational lensing data, developed in the first paper in the series, successfully reconstructs the mass distribution of a simulated cluster. In this paper we apply the method to the ground-based high-quality multi-colour data of RX J1347.5-1145, the most X-ray luminous cluster to date. A new analysis of the cluster core on very deep, multi-colour data analysis of VLT/FORS data reveals many more arc candidates than previously known for this cluster. The combined strong and weak lensing reconstruction confirms that the cluster is indeed very massive. If the redshift and identification of the multiple-image system as well as the redshift estimates of the source galaxies used for weak lensing are correct, we determine the enclosed cluster mass in a cylinder to M(<360 h^-1 kpc)= (1.2 +/- 0.3) 10^15 Msun. In addition the reconstructed mass distribution follows the distribution found with independent methods (X-ray measurements, SZ). With higher resolution (e.g. HST imaging data) more reliable multiple imaging information can be obtained and the reconstruction can be improved to accuracies greater than what is currently possible with weak and strong lensing techniques.
In this paper, we compare three methods to reconstruct galaxy cluster density fields with weak lensing data. The first method called FLens integrates an inpainting concept to invert the shear field with possible gaps, and a multi-scale entropy denoising procedure to remove the noise contained in the final reconstruction, that arises mostly from the random intrinsic shape of the galaxies. The second and third methods are based on a model of the density field made of a multi-scale grid of radial basis functions. In one case, the model parameters are computed with a linear inversion involving a singular value decomposition. In the other case, the model parameters are estimated using a Bayesian MCMC optimization implemented in the lensing software Lenstool. Methods are compared on simulated data with varying galaxy density fields. We pay particular attention to the errors estimated with resampling. We find the multi-scale grid model optimized with MCMC to provide the best results, but at high computational cost, especially when considering resampling. The SVD method is much faster but yields noisy maps, although this can be mitigated with resampling. The FLens method is a good compromise with fast computation, high signal to noise reconstruction, but lower resolution maps. All three methods are applied to the MACS J0717+3745 galaxy cluster field, and reveal the filamentary structure discovered in Jauzac et al. 2012. We conclude that sensitive priors can help to get high signal to noise, and unbiased reconstructions.
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