Space telescopes operating hundreds of thousands of miles from Earth capture vast amounts of data, but how can scientists be sure the signals they detect are genuine cosmic phenomena? NASA’s Artifact InSPECtor project invites the public to help identify and remove data anomalies, directly supporting major space missions like ESA’s Euclid telescope and NASA’s upcoming Nancy Grace Roman Space Telescope in their quest to unravel the mysteries of the universe.
“It’s really cool that we can help teach computers new skills,” said nine-year-old Maeve F., a young participant who tried out the platform. Artifact InSPECtor is open to volunteers of all ages, offering an accessible way for anyone to contribute to astrophysics by training artificial intelligence to filter out errors in telescope data.
Here is how the project works:
The Euclid space telescope, a flagship observatory developed by the European Space Agency (ESA) with significant contributions from NASA, is currently mapping light from millions of distant galaxies. In the coming years, it will be complemented by NASA’s Nancy Grace Roman Space Telescope, which will capture a comparable volume of galaxies across different distances and sky densities. Together, these advanced observatories aim to shed light on the expansion of the universe and the nature of dark energy, the mysterious force driving cosmic acceleration.
To gather the data needed for these cosmological questions, each telescope is equipped with a specialized instrument called a spectrograph. Functioning much like a prism, the spectrograph splits light from individual galaxies—even those billions of light-years away—into a spectrum of colors. By analyzing these spectral patterns, astronomers can determine a galaxy’s distance, its stellar composition, and even properties of the supermassive black holes at its core.
However, before these analyses can proceed, researchers must overcome a critical data challenge.
Telescope imagery is often cluttered with “artifacts”—unwanted signals originating from sources other than actual celestial objects. These artifacts can arise from stray light glinting off the telescope structure, cosmic rays hitting the detector, or electronic quirks in the camera system. Similar to a smudge on a smartphone camera lens or solar glare in a photograph, these anomalies can obscure real scientific data and confuse automated analysis tools.
To filter out these artifacts, astronomers have developed artificial intelligence (AI) tools capable of learning to recognize and flag anomalous signals, much like facial recognition software identifies human features. However, training AI to accurately distinguish artifacts in data from highly advanced, newly calibrated space instruments remains a formidable challenge, as machine models do not always achieve perfect reliability on the first attempt.
This is where public participation becomes crucial. By joining Artifact InSPECtor, volunteers examine actual telescope data from Euclid and, when it begins operations in early 2027, from the Nancy Grace Roman Space Telescope. The project provides tutorials on identifying artifacts, and the classifications made by volunteers are used to train and refine the machine learning algorithms. Through this collaborative effort between human volunteers, AI, and scientists, researchers can unlock unprecedented insights into the fundamental workings of the cosmos.
Citizens with a curiosity for space and a desire to assist scientific discovery can participate using a smartphone, tablet, or computer. Visit Artifact InSPECtor today to begin classifying data and contribute directly to the search for answers about dark energy and the evolution of the universe.
