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      The core of the massive cluster merger MACS J0417.5-1154 as seen by VLT/MUSE

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          Abstract

          We present a multi-wavelength analysis of the core of the massive galaxy cluster MACS\,J0417.5-1154 (\(z = 0.441\); MACS\;J0417). Our analysis takes advantage of VLT/MUSE observations which allow the spectroscopic confirmation of three strongly-lensed systems. One of these, nick-named \emph{The Doughnut}, consists of three complete images of a complex ring galaxy at \(z = 0.8718\) and a fourth, partial and radial image close to the Brightest Cluster Galaxy (BCG) only discernible thanks to its strong [OII] line emission. The best-fit mass model (rms of 0.38\arcsec) yields a two-dimensional enclosed mass of \(M({\rm R < 200\,kpc}) = (1.77\pm0.03)\times10^{14}\,\msun\) and almost perfect alignment between the peaks of the BCG light and the dark matter of (\(0.5\pm0.5\))\arcsec . Our finding that a significant misalignment results when the radial image of \emph{The Doughnut} is omitted serves as an important caveat for studies of BCG-dark matter offsets in galaxy clusters. Using \emph{Chandra} data to map the intra-cluster gas, we observe an offset between the gas and dark-matter peaks of (\(1.7\pm0.5\))\arcsec, and excellent alignment of the X-ray peak with the location of optical emission line associated with the BCG. We interpret all observational evidence in the framework of on-going merger activity, noting specifically that the coincidence between the gas peak and the peak of blue light from the BCG may be evidence of dense, cold gas leading to direct star formation. We use the surface area \(\sigma_{\mu}\) above a given magnification factor \(\mu\) as a metric to estimate the lensing power of MACS\,J0417. We obtain \(\sigma(\mu > 3) = 0.22\)\,arcmin\(^2\) confirming MACS\,J0417 as an efficient gravitational lens. Finally, we discuss the differences between our mass model and Mahler et al. (2018).

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          A Bayesian approach to strong lensing modelling of galaxy clusters

          In this paper, we describe a procedure for modelling strong lensing galaxy clusters with parametric methods, and to rank models quantitatively using the Bayesian evidence. We use a publicly available Markov chain Monte-Carlo (MCMC) sampler ('Bayesys'), allowing us to avoid local minima in the likelihood functions. To illustrate the power of the MCMC technique, we simulate three clusters of galaxies, each composed of a cluster-scale halo and a set of perturbing galaxy-scale subhalos. We ray-trace three light beams through each model to produce a catalogue of multiple images, and then use the MCMC sampler to recover the model parameters in the three different lensing configurations. We find that, for typical Hubble Space Telescope (HST)-quality imaging data, the total mass in the Einstein radius is recovered with ~1-5% error according to the considered lensing configuration. However, we find that the mass of the galaxies is strongly degenerated with the cluster mass when no multiple images appear in the cluster centre. The mass of the galaxies is generally recovered with a 20% error, largely due to the poorly constrained cut-off radius. Finally, we describe how to rank models quantitatively using the Bayesian evidence. We confirm the ability of strong lensing to constrain the mass profile in the central region of galaxy clusters in this way. Ultimately, such a method applied to strong lensing clusters with a very large number of multiple images may provide unique geometrical constraints on cosmology. The implementation of the MCMC sampler used in this paper has been done within the framework of the Lenstool software package, which is publicly available.
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            MUSE Pipeline: the First Year in Operation

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              Author and article information

              Journal
              31 October 2018
              Article
              1811.02505
              7edf9c15-6c9b-43f3-8184-2b8eabdf48b8

              http://arxiv.org/licenses/nonexclusive-distrib/1.0/

              History
              Custom metadata
              14 pages, 4 figures, 6 tables, submitted to MNRAS
              astro-ph.GA

              Galaxy astrophysics
              Galaxy astrophysics

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