# A New Approach to Free-Form Cluster Lens Modeling Inspired by the JPEG Image Compression Method

## TL;DR

This paper introduces a novel free-form galaxy cluster lens modeling method inspired by JPEG image compression, enabling accurate mass distribution modeling with fewer parameters, especially in high-magnification regions.

## Contribution

The paper presents a new JPEG-inspired parametrization technique for free-form cluster lens modeling, improving flexibility and accuracy with fewer parameters compared to existing methods.

## Key findings

- Successfully approximates an N-body simulated cluster.
- Achieves high accuracy in high-magnification regions.
- Reduces the number of parameters needed for modeling.

## Abstract

I propose a new approach to free-form cluster lens modeling that is inspired by the JPEG image compression method. This approach is motivated specifically by the need for accurate modeling of high-magnification regions in galaxy clusters. Existing modeling methods may struggle in these regions due to their limited flexibility in the parametrization of the lens, even for a wide variety of free-form methods. This limitation especially hinders the characterization of faint galaxies at high redshifts, which have important implications for the formation of the first galaxies and even for the nature of dark matter. JPEG images are extremely accurate representations of their original, uncompressed counterparts but use only a fraction of number of parameters to represent that information. Its relevance is immediately obvious to cluster lens modeling. Using this technique, it is possible to construct flexible models that are capable of accurately reproducing the true mass distribution using only a small number of free parameters. Transferring this well-proven technology to cluster lens modeling, I demonstrate that this `JPEG parametrization' is indeed flexible enough to accurately approximate an N-body simulated cluster.