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Improving Lens Modelling from Ground-Based Imaging with Deconvolution

Sep 2026 · Galaxies · Vol 14, pp. 88 · 0 citations · 32 references
Physics

Abstract

Accurate and precise mass modelling of strong lensing systems is essential for extracting insights into cosmology, galaxy environments, and the nature of dark matter. The Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP), which has mapped ∼1000 square degrees of the sky, discovered over 1000 definite or probable galaxy-scale gravitational lens candidates. As the resolution of ground-based imaging poses challenges for accurate lens modelling, high-resolution imaging is traditionally sought after for detailed analyses of these systems. In this work, we instead propose applying the STARRED algorithm, which leverages starlet wavelet regularisation, as a preprocessing step before lens modelling to maximise the scientific output of the large HSC-SSP sample. We test this approach on seven HSC-like mock lensing systems with different lensing configurations. Our results show that the resolution boost from ∼0.6″ to ∼0.15″ enables improves accuracy and sub-3% precision measurements of key lensing parameters such as the Einstein radius, θE, and the mass axis ratio, qm, for ground-based images. These results pave the way for accurate measurements of key strong lensing quantities from a large sample of ground-based observations.

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