Richard, Johan and Natarajan, Priyamvada and Kneib, Jean-Paul and Sharon, Keren and Limousin, Marceau and Jullo, Eric and Jauzac, Mathilde and Niemiec, Anna (2020) 'hybrid-lenstool : a self-consistent algorithm to model galaxy clusters with strong- and weak-lensing simultaneously.', Monthly notices of the Royal Astronomical Society., 493 (3). pp. 3331-3340.
We present a new galaxy cluster lens modelling approach, hybrid-LENSTOOL, that is implemented in the publicly available modelling software LENSTOOL. hybrid-LENSTOOL combines a parametric approach to model the core of the cluster, and a non-parametric (free-form) approach to model the outskirts. hybrid-LENSTOOL optimizes both strong- and weak-lensing constraints simultaneously (Joint-Fit), providing a self-consistent reconstruction of the cluster mass distribution on all scales. In order to demonstrate the capabilities of the new algorithm, we tested it on a simulated cluster. hybrid-LENSTOOL yields more accurate reconstructed mass distributions than the former Sequential-Fit approach where the parametric and the non-parametric models are optimized successively. Indeed, we show with the simulated cluster that the mass density profile reconstructed with a Sequential-Fit deviates from the input by 2–3σ at all scales while the Joint-Fit gives a profile that is within 1–1.5σ of the true value. This gain in accuracy is consequential for recovering mass distributions exploiting cluster lensing and therefore for all applications of clusters as cosmological probes. Finally we found that the Joint-Fit approach yields shallower slope of the inner density profile than the Sequential-Fit approach, thus revealing possible biases in previous lensing studies.
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|Publisher Web site:||https://doi.org/10.1093/mnras/staa473|
|Publisher statement:||This article has been accepted for publication in Monthly notices of the Royal Astronomical Society. ©: 2020 The Author(s) . Published by Oxford University Press on behalf of the Royal Astronomical Society. All rights reserved.|
|Date accepted:||11 February 2020|
|Date deposited:||29 April 2020|
|Date of first online publication:||17 February 2020|
|Date first made open access:||29 April 2020|
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