Euclid Space Warps: Help spot galaxies bending spacetime!

New citizen science project Space Warps lets you study new Euclid space telescope data to find galaxies bending the fabric of the universe. The post Euclid Space Warps: Help spot galaxies bending spacetime! first appeared on EarthSky. The science-journalism coverage adds useful context, while the strongest evidential footing still comes from the underlying data, papers or institutional documentation.

It matters because Earth science becomes stronger when local observations can be placed inside a broader physical pattern that spans time and geography. The planet operates as a coupled system in which atmospheric, oceanic, cryospheric and solid-Earth processes interact across timescales from days to millions of years. A measurement that captures one variable at one location and one moment has limited interpretive value until it is embedded in the longer series and wider spatial coverage that allow natural variability to be separated from forced change. ESA originally published this article on April 21, 2026. With the launch of Space Warps, a new citizen science project, you can now join in the search to find galaxies that are bending the very fabric of the universe.

ESA’s Euclid telescope launched in July 2023 and is revolutionizing the studies of strong gravitational lensing by providing very sensitive imaging over large swaths of the sky. In March 2025, 500 galaxy-galaxy strong lenses were found nestled in just the first 0.04% of Euclid data, most of them previously unknown.

ESA’s Euclid telescope captured galaxy NGC 6505 acting as a gravitational lens, bending the light from a more distant galaxy and creating this Einstein ring. Spot gravitational lenses with Space Warps As Euclid continues its survey, sending around 100 gigabytes of data back to Earth every day, ESA and the Euclid Consortium once again.

For this project, you will be inspecting new high quality imaging data from Euclid in which many previously unknown strong lenses are hiding. About 300, 000 images pre-selected by AI algorithms will be shown, fine-tuned with the results from the initial citizen-science Euclid strong lens search.

The broader interest lies in linking the observation to climatic, geophysical or environmental dynamics that extend well beyond the immediate event or location. Earth science is unusual in that its most important questions operate on timescales that no single research career can observe directly, making the archival record, whether in ice, sediment, rock or satellite data, as important as any new measurement. Results that can be embedded in that record, and that either confirm or challenge the patterns it reveals, carry disproportionate scientific weight.

What we can learn from strong lenses The Euclid mission explores how the universe has expanded and how its structure has changed through cosmic history. In this brand-new Data Release 1 data, 30 times larger than the initial search and together with our improved AI algorithms, we are expecting to find more than 10, 000 high quality.

Because this item comes through EarthSky as science journalism, it should be treated as contextual reporting rather than primary evidence. Good science reporting can identify why a result matters, connect it to the wider literature and make technical work readable, but the decisive evidence remains in the original paper, dataset, mission release or technical record. That distinction is especially important when a story is later repeated by aggregators, because repetition increases visibility, not evidential strength.

The next step is to place the result inside longer time series and to compare it with independent instruments and independent sites. Earth system observations gain most of their interpretive power from network density and temporal depth, not from any single measurement however precise. Model simulations that assimilate the new data will help clarify whether the observation fits comfortably within known natural variability or represents a shift that existing models do not reproduce.

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