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MrMARTIAN: A Multi-resolution Mass Reconstruction Algorithm Combining Free-form and Analytic Components

Sangjun Cha, M. James Jee

TL;DR

MrMARTIAN addresses limitations of purely free-form strong-lensing reconstructions by embedding analytic nodes within a multi-resolution grid. This hybrid approach stabilizes the inner mass profile, reduces oversmoothing, and improves efficiency while preserving flexibility. Across simulations (Ares, Hera) and the real cluster MACS J0416, it yields superior mass and magnification recovery, with robust performance when constraints are sparse and an image-plane rms of ~ $0.11''$ for MACS0416 constrained by 412 images. The work provides publicly available lens models that enhance mass-mapping accuracy and magnification estimates in JWST-era cluster lensing and dark matter studies.

Abstract

We present ${\tt MrMARTIAN}$ (Multi-resolution MAximum-entropy Reconstruction Technique Integrating Analytic Node), a new hybrid strong lensing (SL) modeling algorithm. By incorporating physically motivated analytic nodes into the free-form method ${\tt MARS}$, ${\tt MrMARTIAN}$ enables stable and flexible mass reconstructions while mitigating oversmoothing in the inner mass profile. Its multi-resolution framework increases the degrees of freedom in regions with denser strong lensing constraints, thereby enhancing computational efficiency for a fixed number of free parameters. We evaluate the performance of ${\tt MrMARTIAN}$ using publicly available simulated SL data and find that it consistently outperforms ${\tt MARS}$ in recovering both mass and magnification. In particular, it delivers significantly more stable reconstructions when multiple images are sparsely distributed. Finally, we apply ${\tt MrMARTIAN}$ to the galaxy cluster MACS J0416.1-2403, incorporating two analytic nodes centered on the northeastern and southwestern BCGs. Our mass model, constrained by 412 multiple images, achieves an image-plane rms scatter of ~0".11, the smallest to date for this dataset.

MrMARTIAN: A Multi-resolution Mass Reconstruction Algorithm Combining Free-form and Analytic Components

TL;DR

MrMARTIAN addresses limitations of purely free-form strong-lensing reconstructions by embedding analytic nodes within a multi-resolution grid. This hybrid approach stabilizes the inner mass profile, reduces oversmoothing, and improves efficiency while preserving flexibility. Across simulations (Ares, Hera) and the real cluster MACS J0416, it yields superior mass and magnification recovery, with robust performance when constraints are sparse and an image-plane rms of ~ for MACS0416 constrained by 412 images. The work provides publicly available lens models that enhance mass-mapping accuracy and magnification estimates in JWST-era cluster lensing and dark matter studies.

Abstract

We present (Multi-resolution MAximum-entropy Reconstruction Technique Integrating Analytic Node), a new hybrid strong lensing (SL) modeling algorithm. By incorporating physically motivated analytic nodes into the free-form method , enables stable and flexible mass reconstructions while mitigating oversmoothing in the inner mass profile. Its multi-resolution framework increases the degrees of freedom in regions with denser strong lensing constraints, thereby enhancing computational efficiency for a fixed number of free parameters. We evaluate the performance of using publicly available simulated SL data and find that it consistently outperforms in recovering both mass and magnification. In particular, it delivers significantly more stable reconstructions when multiple images are sparsely distributed. Finally, we apply to the galaxy cluster MACS J0416.1-2403, incorporating two analytic nodes centered on the northeastern and southwestern BCGs. Our mass model, constrained by 412 multiple images, achieves an image-plane rms scatter of ~0".11, the smallest to date for this dataset.

Paper Structure

This paper contains 10 sections, 7 equations, 1 figure.

Table of Contents

  1. Introduction
  2. Data
  3. Mock Cluster Data
  4. MACSJ0416 Data
  5. JWST NIRCam Images
  6. SL Data
  7. Method
  8. Lensing Theory
  9. Truncated Pseudo-Elliptical NFW Profile
  10. MrMARTIAN: Hybrid Lens Modeling Algorithm

Figures (1)

  • Figure 1: Multiple-image distributions and resolution levels for the reconstruction of MACSJ0416. The red (blue) circles indicate the positions of gold (silver) images, while the yellow crosses represent the initial locations of analytic nodes. The red, green, and purple shaded regions illustrate the resolutions of $1\hbox{$.\!\!^{\prime\prime}$}1$/pix, $2\hbox{$.\!\!^{\prime\prime}$}2$/pix, and $8\hbox{$.\!\!^{\prime\prime}$}8$/pix, respectively. The mosaic image is created using the F200W filter.