The revolution in strong lensing discoveries from Euclid

TL;DR

Euclid's high-resolution imaging and wide coverage are set to dramatically increase the number of known strong gravitational lenses, enabling new insights into dark matter, galaxy evolution, and cosmology.

Contribution

This paper reports the first identification of approximately 500 strong lens candidates in Euclid data, demonstrating the effectiveness of machine learning and citizen science in lens discovery.

Findings

Identification of 500 strong lens candidates in early Euclid data

Machine learning models achieve high purity in lens detection

Forecast of over 100,000 strong lenses during Euclid's mission

Abstract

Strong gravitational lensing offers a powerful and direct probe of dark matter, galaxy evolution and cosmology, yet strong lenses are rare: only 1 in roughly 10,000 massive galaxies can lens a background source into multiple images. The European Space Agency's Euclid telescope, with its unique combination of high-resolution imaging and wide-area sky coverage, is set to transform this field. In its first quick data release, covering just 0.45% of the full survey area, around 500 high-quality strong lens candidates have been identified using a synergy of machine learning, citizen science and expert visual inspection. This dataset includes exotic systems such as compound lenses and edge-on disk lenses, demonstrating Euclid's capacity to probe the lens parameter space. The machine learning models developed to discover strong lenses in Euclid data are able to find lenses with high purity rates, confirming that the mission's forecast of discovering over 100,000 strong lenses is achievable during its 6-year mission. This will increase the number of known strong lenses by two orders of magnitude, transforming the science that can be done with strong lensing.