{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/model-independent-mass-reconstruction-of-the","title":"Model-Independent Mass Reconstruction of the Hubble Frontier Field Clusters with MARS Based on Self-Consistent Strong Lensing Data","arxiv_id":"2301.08765","date":"2023-01-20","proceeding":null,"authors":["Sangjun Cha","M. James Jee"],"abstract":"We present new strong-lensing (SL) mass reconstruction of the six Hubble Frontier Fields (HFF) clusters with the MAximum-entropy ReconStruction (${\\tt MARS}$) algorithm. ${\\tt MARS}$ is a new free-form inversion method, which suppresses spurious small-scale fluctuations while achieving excellent convergence in positions of multiple images. For each HFF cluster, we obtain a model-independent mass distribution from the compilation of the self-consistent SL data in the literature. With $100-200$ multiple images per cluster, we reconstruct solutions with small scatters of multiple images in both source (~0\".02) and image planes (~0.\"05-0.''1), which are lower than the previous results by a factor of 5-10. An outstanding case is the MACS J0416.1-2403 mass reconstruction, which is based on the largest high-quality SL dataset where all 236 multiple images/knots have spectroscopic redshifts. Although our solution is smooth on a large scale, it reveals group/galaxy-scale peaks where the substructures are required by the data. We find that in general, these mass peaks are in excellent spatial agreement with the member galaxies, although ${\\tt MARS}$ never uses the galaxy distributions as priors. Our study corroborates the flexibility and accuracy of the ${\\tt MARS}$ algorithm and demonstrates 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 mass reconstruction, and self-consistency within the dataset becomes a critical issue.","url_abs":"https://arxiv.org/abs/2301.08765v4","url_pdf":"https://arxiv.org/pdf/2301.08765v4.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"model-independent-mass-reconstruction-of-the","repo_url":"https://github.com/sang6199/hff_clusters","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"pytorch","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}