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Strong-Lensing Analysis of MACS,J0717.5+3745 from Hubble Frontier Fields observations: How well can the mass distribution be constrained? (1510.08077v2)

Published 27 Oct 2015 in astro-ph.CO and astro-ph.GA

Abstract: [abridged] We present a strong-lensing analysis of MACSJ0717.5+3745, based on the full depth of the Hubble Frontier Field (HFF) observations, which brings the number of multiply imaged systems to 61, ten of which are spectroscopically confirmed. The total number of images comprised in these systems rises to 165. Our analysis uses a parametric mass reconstruction technique, as implemented in the Lenstool software, to constrain a mass distribution composed of four large-scale mass components + galaxy-scale perturbers. We find a superposition of cored isothermal mass components to provide a good fit to the observational constraints, resulting in a very shallow mass distribution for the smooth (large-scale) component. Given the implications of such a flat mass profile, we investigate whether a model composed of "peaky" non-cored mass components can also reproduce the observational constraints. We find that such a non-cored mass model reproduces the observational constraints equally well. Although the total mass distributions of both models are consistent, as well as the integrated two dimensional mass profiles, we find that the smooth and the galaxy-scale components are very different. We conclude that, even in the HFF era, the generic degeneracy between smooth and galaxy-scale components is not broken, in particular in such a complex galaxy cluster. Consequently, insights into the mass distribution of MACS J0717 remain limited, underlining the need for additional probes beyond strong lensing. Our findings also have implications for estimates of the lensing magnification: we show that the amplification difference between the two models is larger than the error associated with either model. This uncertainty decreases the area of the image plane where we can reliably study the high-redshift Universe by 50 to 70%.

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