An American high school student has stunned the scientific world by developing an algorithm to map 1.5 million previously unknown space objects using overlooked NASA data, revolutionising modern citizen science.
In a feat that has left the global astronomical community both humbled and exhilarated, a 17-year-old American high school student has achieved what many professional research teams spend decades attempting.
By leveraging advanced data processing techniques and publicly available satellite imagery, this young researcher has successfully mapped 1.5 million previously unidentified objects in space, ranging from distant asteroids to faint star clusters and potential orbital debris.
Matteo Paz, a student at Pasadena High School, undertook the project during a summer program at Planet Finder Academy in 2022. The program designed to immerse students in real-world astronomy challenges, provided Paz with access to massive datasets and mentorship from leading astronomers including Davy Kirkpatrick at the Infrared Processing and Analysis Centre (IPAC). Paz’s discovery earned him over $250,000 in awards and has opened new avenues for astronomers studying variable cosmic phenomena.
Decoding NASA’s ‘dark’ data
The NEOWISE mission, launched in 2009, scanned the sky in infrared light over a decade, amassing nearly 200 billion individual measurements. While the initial purpose of the mission was to track near-Earth asteroids, the dataset also contained signals from distant galaxies, stars and cosmic events. Paz took on the challenge of analysing this vast archive by developing an automated machine-learning system capable of detecting subtle variations in brightness over time.
The breakthrough did not come from peering through a traditional telescope, but rather through the meticulous “mining” of massive datasets provided by NASA and other space agencies. These agencies collect petabytes of information every year far more than their internal teams can manually analyse. This surplus of information, often referred to as “dark data,” contains hidden gems that remain tucked away in digital archives.
The student developed a custom algorithm designed to filter out “noise” atmospheric interference and sensor glitches that typically obscures smaller or dimmer objects. While professional software often ignores these marginal data points to avoid false positives, the student’s refined approach allowed for the identification of anomalies that had been overlooked for years.
By cross-referencing archival infrared data with recent optical surveys, the mapping project revealed a crowded neighbourhood in our solar system and beyond that scientists didn’t realise was so densely populated.
Implications for astronomy and data science
Experts say the discovery is significant not just for its sheer scale, but also for what it represents: the democratisation of big data in science. By leveraging computational tools, young researchers can now contribute meaningfully to fields previously dominated by professional scientists.
The project demonstrates the potential of applying coding, mathematics, and automated analysis to massive scientific datasets, uncovering patterns that would otherwise remain hidden.
Astronomers are particularly excited about the discovery of variable and transient objects, which provide crucial clues about short-lived cosmic phenomena. These findings could help refine models of stellar lifecycles, supernova mechanics, and other rare events, ultimately improving our understanding of the universe’s evolution.
For Paz, the journey began as a high school summer project but has now placed him at the forefront of astronomical research. His success underscores the value of mentorship, computational skills, and curiosity-driven exploration in advancing modern science. As NASA continues to release archival data from missions like NEOWISE, experts predict that more young innovators will follow in his footsteps, accelerating discoveries in astronomy and beyond.
Shaking the foundations of traditional research
The scientific community is now grappling with the fact that a teenager, working from a home desk, has managed to expand our known map of the universe by such a massive margin. It raises vital questions about how space agencies manage their data and whether current AI models used by these institutions are being utilized to their full potential.
While the student remains humble, citing a passion for coding and a curiosity about the “gaps in the maps,” the world’s leading universities are already taking notice. This discovery isn’t just about 1.5 million objects; it is about the realisation that the next great leap in our understanding of the cosmos might not come from a laboratory, but from the bedroom of a student who dared to look at the numbers differently.
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