A while ago, we ran a project lead by Jimena Gonzalez Lozano ran the FIRST machine learning+citizen inspection system to find strong gravitational lenses searching all of galaxies in the Dark Energy Survey.

The machine learning model makes use of the transformer encoder, which is based on the attention mechanism. Transformers were originally designed for natural language processing tasks. However, they can also be employed in image-processing tasks — like facial recognition in photographs — that in our case score images on their likelihood of being a gravitational lens. All of you then helped to sift through these likely candidates producing amazing results! A few words from Jimena…

Thank You for Helping Us Discover Hundreds of Strong Lenses!

Thanks to the incredible efforts of hundreds of volunteers who classified over 20,000 images, we have identified hundreds of strong gravitational lenses! After carefully reviewing the highest-scored images, we classified the final candidates into three categories based on confidence:
• 149 “definite” lenses
• 516 “probable” lenses
• 663 “could-be” lenses

You can find the full results in our publication available on arXiv, where Figures 12–15 showcase examples of candidates from each confidence category. Below is an image highlighting some of the high-confidence strong lenses that had not been identified before!

This project holds the record for finding the most strong lenses in the Dark Energy Survey. Additionally, we found that our machine learning methodology produces significantly fewer false positives (incorrect lens classifications) than previous techniques. This makes it a powerful tool for the next generation of astronomical surveys, where we will be dealing with massive amounts of data.

Importantly, even the images classified as not being lenses are valuable! They can be used to train future machine learning models, helping refine and improve their accuracy.

Finally, here is a collage showcasing the incredible diversity of strong lenses discovered in this project—featuring a variety of shapes, sizes, and colors.

A collage of strong lenses that you helped to identify! This image was the winning entry in the UW-Madison 2023 Cool Science Image Contest.

Thank you once again for your time and dedication. Your contributions have made a real impact on the search for these rare cosmic phenomena!

Jimena and the Space Warps Team