Simulation Of The Microlensing Effect Near The Critical Curve Of The Galaxy Cluster

TL;DR

This paper presents an efficient GPU-based simulation method for modeling microlensing effects near the critical curves of galaxy clusters, enabling detailed analysis of dark matter detection prospects.

Contribution

The authors developed a GPU-optimized interpolation method to simulate microlensing with high accuracy and computational efficiency near critical curves.

Findings

Generated 80 magnification maps for statistical analysis.

Simulated effects of 13,000 microlenses with 10^13 rays in about 7000 seconds.

Analyzed microcaustic density and peak magnification distributions.

Abstract

In the smooth mass distribution model, the critical curve represents a line with magnification divergence on the image plane in a strong gravitational lensing system. Considering the microlensing effects caused by discrete masses, the magnification map in the source plane exhibits a complex structure, which offers a promising way for detecting dark matter. However, simulating microlensing near the critical curve poses challenges due to magnification divergence and the substantial computational demands involved. To achieve the required simulation accuracy, direct inverse ray-shooting would require significant computational resources. Therefore we applied a GPU-based code optimized with interpolation method to enable efficient computation on a large scale. Using the GPU of NVIDIA Tesla V100S PCIe 32GB, it takes approximately 7000 seconds to calculate the effects of around 13,000 microlenses for a simulation involving 1013 emitted rays. Then we generated 80 magnification maps, and select 800 light curves for a statistical analysis of microcaustic density and peak magnification.