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CANUCS: Constraining the MACS J0416.1-2403 Strong Lensing Model with JWST NIRISS, NIRSpec and NIRCam (2406.10332v2)

Published 14 Jun 2024 in astro-ph.CO and astro-ph.GA

Abstract: (Abridged) The strong lensing models of galaxy clusters rely on the number and quality of multiple images with spectroscopic redshifts. We present an updated strong lensing model of MACS J0416.1-2403 with the largest sample of multiple images with spectroscopic redshifts in a galaxy cluster field to date. Furthermore, we aim to demonstrate the effectiveness of JWST, particularly its NIRISS camera, for strong lensing studies. We used NIRCam imaging and NIRSpec and NIRISS spectroscopy from the CAnadian NIRISS Unbiased Cluster Survey (CANUCS). The cluster mass model was constrained using Lenstool software. Our new dataset, which we used for constraining the lens model, comprises 303 secure multiple images with spectroscopic redshifts from 111 background sources and includes 95 systems with previously known MUSE redshift and 16 systems (with 46 multiple images) for which we obtained spectroscopic redshift for the first time using NIRISS and NIRSpec spectroscopy. Three of the spectroscopic systems were not identified by previous JWST studies. The total number of secure spectroscopic systems is more than 20% higher than in the previous strong lensing studies of this cluster. The model can reproduce multiple images with the root-mean-square distance of ~ 0.52''. We also provide a full catalogue with 415 multiple images, including less reliable candidates. In total, we provide 15 new multiple-image system candidates (with 38 multiple images) not reported in previous studies. Furthermore, we demonstrate the effectiveness of JWST, particularly NIRISS, for obtaining spectroscopic redshifts of multiple images. As NIRISS F115W, F150W, and F200W grism spectroscopy captures at least two of the [OII], [OIII] and H${\alpha}$ lines at 1 < z < 3 (a redshift range particularly relevant for strong lensing studies) without target pre-selection, it complements MUSE and NIRSpec observations extremely well.

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