CURLING

III. Identifying candidate wide-separation gravitationally lensed quasars from the CatNorth catalogue

¹ National Astronomical Observatories, Chinese Academy of Sciences, 20A Datun Road, Chaoyang District, Beijing 100101, China
² School of Astronomy and Space Science, University of Chinese Academy of Sciences, Beijing 100049, China
³ Department of Physics, Nanchang University, Nanchang 330031, China
⁴ Center for Relativistic Astrophysics and High Energy Physics, Nanchang University, Nanchang 330031, China
⁵ Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing, Jiangsu 210023, China
⁶ Key Laboratory of Space Astronomy and Technology, National Astronomical Observatories, Chinese Academy of Sciences, 20A Datun Road, Chaoyang District, Beijing 100101, China
⁷ Kavli Institute for Astronomy and Astrophysics, Peking University, Yi He Yuan Lu 5, Haidian Qu, 100871 Beijing, China
⁸ Department of Astronomy, School of Physics, Peking University, Beijing 100871, China
⁹ Leiden Observatory, Leiden University, Leiden, The Netherlands
¹⁰ Kapteyn Astronomical Institute, University of Groningen, PO Box 800, 9700 AV Groningen, The Netherlands

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Received: 23 November 2025
Accepted: 1 April 2026

Abstract

Aims. Wide-separation lensed quasars (WSLQs) represent a special but rare subclass of strongly lensed quasars with multiple images, magnified by massive galaxy cluster lenses, which offer valuable probes for the properties of dark matter halos and detailed characteristics of quasar host galaxies. However, only around ten WSLQ systems are known so far, limiting the development of relevant investigations.

Methods. To enlarge the sample of WSLQs by mining candidates from large-scale sky surveys, we develop a catalogue-based pipeline and apply it to the CatNorth, which is a quasar candidate catalogue with more than 1.5 million candidates constructed from Gaia DR3. The CatNorth has a purity of ~90% and a limiting magnitude in the Gaia G band of ≲21.

Results. Our pipeline unfolds in three sequential stages. First, to search for groups of quasar candidates with a maximum quasar image separation between 10 and 72 arcsec, we applied a friends-of-friends-like algorithm to the HEALPix grids of CatNorth objects using a grid size of 25.6 arcsec. Second, these identified groups undergo an automatic filtering process that assesses the intra-group similarity of photometric colours or spectral information when available. These two steps yield 14 760 quasar candidate groups, while retaining all discoverable previously known WSLQs. Third, a visual inspection, guided primarily by the projected geometry of the quasar images and plausible foreground objects, yields the final candidate sample, with a label indicating the candidates’ quality.

Conclusions. We have identified a total of 333 new WSLQ candidates with separations ranging from 10 to 56.8 arcsec. By exploiting the available SDSS DR16/DESI DR1 spectroscopic data, we uncovered two novel WSLQ candidate systems, but 331 WSLQ candidates - 45 Grade A, 98 Grade B, and 188 Grade C systems - lack sufficient spectral information. In addition, a sample of 29 dual quasar candidates is presented as a by-product. When feasible, we plan to secure follow-up spectroscopy and deeper imaging to confirm WSLQs from the above candidates and proceed with pertinent scientific investigations.