Precision MARS Mass Reconstruction of A2744: Synergizing the Largest Strong-lensing and Densest Weak-lensing JWST

Cha, Sangjun ; HyeongHan, Kim ; Scofield, Zachary P. ; Joo, Hyungjin ; Jee, M. James

We present a new high-resolution free-form mass model of A2744 that combines both weak-lensing (WL) and strong-lensing (SL) data sets from JWST. The SL data set comprises 286 multiple images, presenting the most extensive SL constraint to date for a single cluster. The WL data set, employing photo-z selection, yields a source density of  ∼350arcmin−2, marking the densest WL constraint ever. The combined mass reconstruction enables the highest-resolution mass map of A2744 within the ∼1.8 Mpc × 1.8 Mpc reconstruction region to date, revealing an isosceles triangular structure with two legs of ∼1 Mpc and a base of ∼0.6 Mpc. Although our algorithm, which is called MAximum-entropy ReconStruction (MARS), is entirely blind to the cluster galaxy distribution, the resulting mass reconstruction traces the brightest cluster galaxies remarkably well. The five strongest mass peaks coincide with the five most luminous cluster galaxies within ≲2″. 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 scatter of SL multiple images in both source (∼0.″05) and image (∼0.″1) planes, which is lower than in previous studies by a factor of ∼4. Although MARS represents the mass field with an extremely large number of free parameters (∼300,000), it converges to a solution within a few hours because we use a deep-learning technique. We make our mass and magnification maps publicly available.

https://ui.adsabs.harvard.edu/abs/2024ApJ...961..186C/abstract