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However, these methods are often constrained by their dependence on optimizing a fixed distance function, which can result in the loss of intricate details crucial for astrophysical analysis. In this work, we introduce <jats:monospace>DiffLense<\/jats:monospace>, a novel super-resolution pipeline based on a conditional diffusion model specifically designed to enhance the resolution of gravitational lensing images obtained from the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP). Our approach adopts a generative model, leveraging the detailed structural information present in Hubble space telescope (HST) counterparts. The diffusion model, trained to generate HST data, is conditioned on HSC data pre-processed with denoising techniques and thresholding to significantly reduce noise and background interference. This process leads to a more distinct and less overlapping conditional distribution during the model\u2019s training phase. We demonstrate that <jats:monospace>DiffLense<\/jats:monospace> outperforms existing state-of-the-art single-image super-resolution techniques, particularly in retaining the fine details necessary for astrophysical analyses.<\/jats:p>","DOI":"10.1088\/2632-2153\/ad76f8","type":"journal-article","created":{"date-parts":[[2024,9,3]],"date-time":"2024-09-03T22:58:06Z","timestamp":1725404286000},"page":"035076","update-policy":"https:\/\/doi.org\/10.1088\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["DiffLense: a conditional diffusion model for super-resolution of gravitational lensing data"],"prefix":"10.1088","volume":"5","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6609-3495","authenticated-orcid":true,"given":"Pranath","family":"Reddy","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1205-4033","authenticated-orcid":false,"given":"Michael W","family":"Toomey","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-3431-4269","authenticated-orcid":false,"given":"Hanna","family":"Parul","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6222-8102","authenticated-orcid":false,"given":"Sergei","family":"Gleyzer","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"266","published-online":{"date-parts":[[2024,9,19]]},"reference":[{"key":"mlstad76f8bib1","doi-asserted-by":"publisher","first-page":"587","DOI":"10.1046\/j.1365-8711.1998.01319.x","volume":"295","author":"Mao","year":"1998","journal-title":"Mon. 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