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MAximum-entropy ReconStruction (MARS): A New Strong-lensing Reconstruction Algorithm for the JWST Era

Published online by Cambridge University Press:  04 March 2024

Sangjun Cha Open the ORCID record for Sangjun Cha [Opens in a new window]  and
M. James Jee
Sangjun Cha*
Affiliation:
Department of Astronomy, Yonsei University, 50 Yonsei-ro, Seoul 03722, Korea.
M. James Jee
Affiliation:
Department of Astronomy, Yonsei University, 50 Yonsei-ro, Seoul 03722, Korea. Department of Physics and Astronomy, University of California, Davis, One Shields Avenue, Davis, CA 95616, USA
*
email: sang6199@yonsei.ac.kr
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Abstract

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The MAximum-entropy ReconStruction (MARS) method is a free-form strong-lensing (SL) reconstruction algorithm, which adopts the maximum cross-entropy as a regularization. MARS shows remarkable convergence of multiple images in both source (∼0.”02) and image planes (∼0.”05 – 0.”1) while suppressing spurious fluctuations. Although the reconstruction requires a large number of free parameters exceeding ∼19,000, our implementation through PyTorch can obtain the reconstruction within hours. From our test using the publicly available synthetic clusters, we have verified that the reconstructed radial mass profiles are consistent with the truth within 1 percent. This makes MARS one of the best-performing SL reconstruction methods. We apply MARS to the six Hubble Frontier Fields clusters and present new mass reconstruction results. We also reconstruct a mass model of Abell 2744 using both weak-lensing (WL) and SL data from the JWST observations, with the largest dataset of Abell 2744, including 286 SL multiple images and ∼350 arcmin−2 WL constraints.

Keywords

Dark matter distributionGalaxy clustersWeak gravitational lensingStrong gravitational lensing
Type
Poster Paper
Information
Proceedings of the International Astronomical Union , Volume 18 , Symposium S381: Strong Gravitational Lensing in the Era of Big Data , December 2022 , pp. 102 - 105
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Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2024. Published by Cambridge University Press on behalf of International Astronomical Union

References

Bartelmann, M., & Schneider, P. 2001, PhR, 340, 291 Google Scholar
Bergamini, P., Acebron, A., Grillo, E., et al. 2023, ApJ, 952, 84 CrossRefGoogle Scholar
Bezanson, R., Labbe, I., Whitaker, K. E., et al. 2022, arXiv:2212.04026Google Scholar
Cha, S., & Jee, M. J. 2022, ApJ, 931, 127 CrossRefGoogle Scholar
Cha, S., & Jee, M. J. 2023, ApJ, 951, 140 CrossRefGoogle Scholar
Eckert, D., Jauzac, M., Shan, H., et al. 2015, Nature, 528, 105 CrossRefGoogle Scholar
Furtak, L. J., Zitrin, A., Weaver, J. R., et al. 2023, MNRAS, 523, 4568 Google Scholar
Kenib, J. -P., & Natarajan, P. 2011, A&ARv, 19, 47 Google Scholar
Meneghetti, M., Natarajan, P., Coe, D., et al. 2017, MNRAS, 483, 195 Google Scholar
Weaver, J. R., Cutler, S. E., Pan, R., et al. 2023, arXiv:2301.02671Google Scholar
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