Model-independent Mass Reconstruction of the Hubble Frontier Field Clusters with MARS Based on Self-consistent Strong-lensing Data
We present a new strong-lensing (SL) mass reconstruction of the six Hubble Frontier Fields (HFF) clusters with the MAximum-entropy ReconStruction ( MARS ) algorithm. MARS is a new free-form inversion method, which suppresses spurious small-scale fluctuations while achieving excellent convergence in...
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| Format: | Article |
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IOP Publishing
2023-01-01
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| Series: | The Astrophysical Journal |
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| Online Access: | https://doi.org/10.3847/1538-4357/acd111 |
| _version_ | 1797698213545771008 |
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| author | Sangjun Cha M. James Jee |
| author_facet | Sangjun Cha M. James Jee |
| author_sort | Sangjun Cha |
| collection | DOAJ |
| description | We present a new strong-lensing (SL) mass reconstruction of the six Hubble Frontier Fields (HFF) clusters with the MAximum-entropy ReconStruction ( MARS ) algorithm. 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 data set 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 MARS never uses the galaxy distributions as priors. Our study corroborates the flexibility and accuracy of the MARS algorithm and demonstrates that MARS is a powerful tool in the JWST era, when a 2–3 times larger number of multiple image candidates become available for SL mass reconstruction, and self-consistency within the data set becomes a critical issue. |
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| institution | Directory Open Access Journal |
| issn | 1538-4357 |
| language | English |
| last_indexed | 2024-03-12T03:51:00Z |
| publishDate | 2023-01-01 |
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| series | The Astrophysical Journal |
| spelling | doaj.art-d87d7e9cb64c4d58b1cd0d8ad05aa5b22023-09-03T12:22:32ZengIOP PublishingThe Astrophysical Journal1538-43572023-01-01951214010.3847/1538-4357/acd111Model-independent Mass Reconstruction of the Hubble Frontier Field Clusters with MARS Based on Self-consistent Strong-lensing DataSangjun Cha0https://orcid.org/0000-0001-7148-6915M. James Jee1https://orcid.org/0000-0002-5751-3697Department of Astronomy, Yonsei University , 50 Yonsei-ro, Seoul 03722, Republic of Korea ; sang6199@yonsei.ac.krDepartment of Astronomy, Yonsei University , 50 Yonsei-ro, Seoul 03722, Republic of Korea ; sang6199@yonsei.ac.kr; Department of Physics and Astronomy, University of California , Davis, One Shields Avenue, Davis, CA 95616, USA ; mkjee@yonsei.ac.krWe present a new strong-lensing (SL) mass reconstruction of the six Hubble Frontier Fields (HFF) clusters with the MAximum-entropy ReconStruction ( MARS ) algorithm. 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 data set 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 MARS never uses the galaxy distributions as priors. Our study corroborates the flexibility and accuracy of the MARS algorithm and demonstrates that MARS is a powerful tool in the JWST era, when a 2–3 times larger number of multiple image candidates become available for SL mass reconstruction, and self-consistency within the data set becomes a critical issue.https://doi.org/10.3847/1538-4357/acd111Dark matter distributionStrong gravitational lensingGalaxy clusters |
| spellingShingle | Sangjun Cha M. James Jee Model-independent Mass Reconstruction of the Hubble Frontier Field Clusters with MARS Based on Self-consistent Strong-lensing Data The Astrophysical Journal Dark matter distribution Strong gravitational lensing Galaxy clusters |
| title | Model-independent Mass Reconstruction of the Hubble Frontier Field Clusters with MARS Based on Self-consistent Strong-lensing Data |
| title_full | Model-independent Mass Reconstruction of the Hubble Frontier Field Clusters with MARS Based on Self-consistent Strong-lensing Data |
| title_fullStr | Model-independent Mass Reconstruction of the Hubble Frontier Field Clusters with MARS Based on Self-consistent Strong-lensing Data |
| title_full_unstemmed | Model-independent Mass Reconstruction of the Hubble Frontier Field Clusters with MARS Based on Self-consistent Strong-lensing Data |
| title_short | Model-independent Mass Reconstruction of the Hubble Frontier Field Clusters with MARS Based on Self-consistent Strong-lensing Data |
| title_sort | model independent mass reconstruction of the hubble frontier field clusters with mars based on self consistent strong lensing data |
| topic | Dark matter distribution Strong gravitational lensing Galaxy clusters |
| url | https://doi.org/10.3847/1538-4357/acd111 |
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