James Webb Space Telescope Feed Post

Precision MARS Mass Reconstruction of Abell 2744: Synergizing the Largest Strong Lensing and Densest Weak Lensing Datasets from JWST

WL + SL Mass reconstruction of A2744. The blue intensity region represents the mass distributions from the WL + SL mass map. The red intensity region corresponds to X-ray surface brightness (OBSID: 7915, 8477 and 8557; PI: J. Kempner). The green region displays radio continuum from radio observations (Venturi et al. 2013; Paul et al. 2019, ; GMRT data at 325MHz). The color composite image is created using the Subaru/Suprime-Cam observations, with the z band for red, R band for green, and B band for blue (Finner & Jee 2022). The areas enclosed with white solid lines indicate the four known radio relics (Pearce et al. 2017; Rajpurohit et al. 2021). The orange solid lines show the expected merger axes from the mass bridges. The FOV is 13. ' 46 × 13. ' 46. Abstract: We present a new high-resolution free-form mass model of Abell 2744, combining both weak-lensing (WL) and strong-lensing (SL) datasets from JWST. The SL dataset comprises 286 multiple images, presenting the most extensive SL constraint to date for a single cluster. The WL dataset, employing photo-z selection, yields a source density of ~ 350 arcmin-2, marking the densest WL constraint ever. The combined mass reconstruction enables the highest-resolution mass map of Abell 2744 within the ~ 1.8 Mpc×1.8 Mpc reconstruction region to date, revealing the isosceles triangular structure with two legs of ~ 1 Mpc and a base of ~ 0.6 Mpc. Although our algorithm MAximum-entropy ReconStruction (MARS) is entirely blind to the cluster galaxy distribution, the resulting mass reconstruction remarkably well traces the brightest cluster galaxies with the five strongest mass peaks coinciding with the five most luminous cluster galaxies. We do not detect any unusual mass peaks that are not traced by the cluster galaxies, unlike the findings in previous studies. Our mass model shows the smallest scatters of SL multiple images in both source (~0".05) and image (~0".1) planes, which are lower than the previous studies by a factor of ~ 4. Although MARS represents the mass field with an extremely large number of ~ 300,000 free parameters, it converges to a solution within a few hours thanks to our utilization of the deep learning technique. We make our mass and magnification maps publicly available.