Researchers working with early Euclid space telescope images report 72 additional galaxy–galaxy strong lens candidates in the mission’s Quick Release 1 data. Strong lensing happens when a massive foreground galaxy bends light from a background galaxy and creates arcs, rings, or multiple images. The new set includes 38 “grade A” confident candidates and 34 “grade B” probable ones. The team also shows that an earlier selection step had unintentionally excluded a class of bright, low‑redshift lenses, so these objects had been missed before.

The candidates come from a search of 63.1 square degrees of Euclid imaging. The team used two independent approaches. One combined machine‑learning models with expert visual checks. The other was a purely human visual search aimed at objects the machine step had excluded. The earlier exclusion involved objects listed in the Gaia catalogue, and it led to missing more than 10% extra lens candidates compared to the first SLDE catalogue.

The paper reports that detailed, semi‑automated lens modelling—fitting simple mass models to the images—confirms at least 41 of the 72 systems so far. That confirmation rate is similar to what the authors found in an earlier SLDE study (315 confirmed out of 488 candidates). The new sample contains some interesting configurations: several edge‑on disc galaxy lenses, sources with arcs close to the lens centre, “red” background sources, and one case where an edge‑on disk lenses a galaxy merger to produce both an Einstein ring (a near‑complete ring of light formed when alignment is close) and a separate doubly imaged feature.

The data come from Euclid’s VISible instrument (VIS), which images optical light from about 550 to 900 nanometres with 0.1 arcsecond pixels, and the Near‑Infrared Spectrometer and Photometer (NISP), which covers roughly 950–2020 nanometres. For each candidate the team extracted 10×10 arcsecond image cutouts. Because wide surveys produce large files, the group commonly used compressed JPEG versions of the images and several visualization styles to help inspectors spot lensing patterns.