MARS: A New Maximum-entropy-regularized Strong Lensing Mass Reconstruction Method

Sangjun Cha, M. James Jee

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)

Abstract

Free-form strong-lensing (SL) mass reconstructions typically suffer from overfitting, which manifests itself as false-positive small-scale fluctuations. We present a new free-form MAximum-entropy ReconStruction (MARS) method without the assumption that light traces mass (LTM). The MARS algorithm enables us to achieve excellent convergence in source positions (∼0.″001), minimize spurious small-scale fluctuations, and provide a quasi-unique solution independently of initial conditions. Our method is tested with the publicly available synthetic SL data FF-SIMS. The comparison with the truth shows that the mass reconstruction quality is on par with those of the best-performing LTM methods published in the literature, which have been demonstrated to outperform existing free-form methods. In terms of the radial mass profile reconstruction, we achieve <1% agreement with the truth for the regions constrained by multiple images. Finally, we apply MARS to A1689 and find that the cluster mass in the SL regime is dominated by the primary halo centered on the brightest cluster galaxy and the weaker secondary halo is also coincident with the bright cluster member ∼160 kpc northeast. Within the SL field, the A1689 radial profile is well described by a Navarro-Frenk-White profile with c 200 = 5.53 ± 0.77 and r s = 538 − 100 + 90 kpc, and we find no evidence that A1689 is overconcentrated.

Original languageEnglish
Article number127
JournalAstrophysical Journal
Volume931
Issue number2
DOIs
Publication statusPublished - 2022 Jun 1

Bibliographical note

Publisher Copyright:
© 2022. The Author(s). Published by the American Astronomical Society.

All Science Journal Classification (ASJC) codes

  • Astronomy and Astrophysics
  • Space and Planetary Science

Fingerprint

Dive into the research topics of 'MARS: A New Maximum-entropy-regularized Strong Lensing Mass Reconstruction Method'. Together they form a unique fingerprint.

Cite this