Euclid Quick Data Release (Q1). The Strong Lensing Discovery Engine F -- Bright and low-redshift strong lenses
Euclid Collaboration: L. R. Ecker (1, 2), M. Fabricius (2, 1), S. Seitz (1, 2), R. Saglia (1, 2), N. E. P. Lines (3), P. Holloway (3), T. Li (3), A. Verma (4), F. Balzer (2), Q. Jin (1), A. Manj\'on-Garc\'ia (5), S. H. Vincken (6), J. Wilde (7), J. A. Acevedo Barroso (8, 9)

TL;DR
This paper reports 72 new galaxy-galaxy strong lens candidates from Euclid data, highlighting the importance of combined machine learning and visual inspection methods, and expanding the expected high-confidence lens count in the Euclid survey.
Contribution
It introduces a new set of strong lens candidates identified through combined search techniques, improving the completeness of the Euclid lens catalog.
Findings
72 new strong lens candidates identified
At least 41 systems confirmed through semi-automated modelling
Expected high-confidence lens count increased to 120,000
Abstract
We present 72 additional galaxy-galaxy strong lenses that complement the sample discovered in the Euclid Quick Release 1 data (63.1 deg^2) of the Strong Lens Discovery Engine (SLDE) papers A-E. It is shown that previous pre-selection of potential lenses, which excluded objects from the Gaia catalogue, led to missing several bright and low-redshift strong lenses, adding more than 10% new strong lens candidates compared to the previous search. In total, the catalogue includes 38 "grade A" (confident) and 34 "grade B" (probable) candidates. These lenses are identified through a combination of two independent searches for bright nearby objects: one based on machine-learning models followed by expert visual inspection, and the other based solely on expert visual inspection, targeting objects not included in the initial machine-learning selection (a limitation identified only after extensive…
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