English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

We present new strong-lensing (SL) mass reconstruction of the six HubbleFrontier Fields (HFF) clusters with the MAximum-entropy ReconStruction (${\ttMARS}$) algorithm. ${\tt MARS}$ is a new free-form inversion method, whichsuppresses spurious small-scale fluctuations while achieving excellentconvergence in positions of multiple images. For each HFF cluster, we obtain amodel-independent mass distribution from the compilation of the self-consistentSL data in the literature. With $100-200$ multiple images per cluster, wereconstruct solutions with small scatters of multiple images in both source(~0".02) and image planes (~0."05-0.''1), which are lower than the previousresults by a factor of 5-10. An outstanding case is the MACS J0416.1-2403 massreconstruction, which is based on the largest high-quality SL dataset where all236 multiple images/knots have spectroscopic redshifts. Although our solutionis smooth on a large scale, it reveals group/galaxy-scale peaks where thesubstructures are required by the data. We find that in general, these masspeaks are in excellent spatial agreement with the member galaxies, although${\tt MARS}$ never uses the galaxy distributions as priors. Our studycorroborates the flexibility and accuracy of the ${\tt MARS}$ algorithm anddemonstrates that ${\tt MARS}$ is a powerful tool in the JWST era, when $2-3$times larger number of multiple image candidates become available for SL massreconstruction, and self-consistency within the dataset becomes a criticalissue.

Model-Independent Mass Reconstruction of the Hubble Frontier Field Clusters with MARS Based on Self-Consistent Strong Lensing Data