NASA and the European Space Agency’s (ESA) Euclid space telescope have begun capturing millions of galaxy images, including rare “clumpy” galaxies known for intense star formation. To analyze this vast data, scientists have launched Galaxy Zoo: Clump Scout II, a citizen science project inviting the public to help refine machine learning tools that identify star-forming clumps within these galaxies.
What happened
In the mid-20th century, astronomers discovered clumpy galaxies—galaxies containing bright, irregular blobs that are massive stellar nurseries where stars form rapidly. These clumpy galaxies were common earlier in the universe but have become rare, and the reasons for their disappearance remain unclear.
Euclid’s mission, with significant NASA contributions, now provides millions of high-resolution galaxy images, including detailed views of these clumpy galaxies. Due to the sheer volume of this data, researchers use machine learning algorithms previously trained with data from Galaxy Zoo: Clump Scout to identify star-forming clumps.
However, the AI occasionally mislabels features caused by distant stars or image artifacts. In Galaxy Zoo: Clump Scout II, volunteer participants review these AI-labeled images, adjusting, deleting, or adding boxes around clumps to improve the machine’s accuracy.
Participants can contribute from any device with internet access, allowing the public to play a direct role in advancing our understanding of how stellar nurseries form and evolve.
Why it matters
Studying clumpy galaxies helps astronomers uncover how star formation processes operated in the early universe and why these galaxies have nearly vanished today. Improving AI-based identification methods enables faster, more accurate analysis of massive astronomical datasets, accelerating discoveries about galaxy evolution.
Engaging citizen scientists in this effort democratizes research and enhances machine learning reliability across other large-scale space data projects.
Background
Clumpy galaxies were first characterized decades ago as irregular galaxies featuring intense star formation in bright regions or clumps. Their prominence in the early cosmos contrasts with their scarcity nearby, posing unanswered questions about galaxy maturation and star formation dynamics.
The Euclid space telescope, launched by ESA with NASA contributions, aims to map the geometry of the dark universe by surveying billions of galaxies. Its data offers unprecedented opportunities to study galaxy morphology, including clumpy structures, on a scale unattainable by ground-based observations.
Galaxy Zoo projects have a history of enlisting volunteers to classify galaxies visually, helping train AI systems for automated analysis.
Sources
This article is based on reporting and publicly available information from the following source:
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