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Innovation #innovation · USA/NASA February 19, 2026

High School Senior Maps 1.5 Million Hidden Cosmic Objects

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High School Senior Maps 1.5 Million Hidden Cosmic Objects

A Teenager Just Unlocked a Decade of Astronomical Data No One Could Read

A 17-year-old from Pasadena High School has accomplished what professional astronomers couldn't: extracting 1.5 million previously hidden variable cosmic objects from the NEOWISE telescope's decade-long infrared survey. Working under mentor Davy Kirkpatrick at Caltech, Matteo Paz developed an artificial intelligence model called VARnet that cracked open an archive containing 200 billion individual detections—data so vast that conventional analysis methods simply couldn't handle it.

The breakthrough matters because variable objects—quasars that flicker, stars that pulse, binary systems that eclipse—hold keys to understanding stellar evolution, transient events, and the dynamic universe. Until now, these objects were buried in plain sight, their signal lost in the noise of sheer abundance. Paz's work transforms a storage problem into actionable science.

How a Summer Project Became Peer-Reviewed Research

Paz arrived at Kirkpatrick's lab in summer 2023 through Caltech's Summer Research Connection program, already an unusual student: he'd completed AP Calculus in eighth grade and was already studying undergraduate-level mathematics. His secondary school elective in coding and theoretical computer science had introduced him to machine learning. On day one, he told Kirkpatrick he wanted to publish a paper. Kirkpatrick didn't laugh.

Kirkpatrick's mentoring philosophy was shaped by his own experience—a Tennessee chemistry and physics teacher named Marilyn Morrison identified his potential and mapped his path to becoming an astronomer. Decades later, he channeled that same approach with Paz, connecting him to Caltech researchers Shoubaneh Hemmati, Daniel Masters, Ashish Mahabal, and Matthew Graham, who provided expertise in machine learning for time-domain astronomy.

The collaboration revealed a critical limitation: NEOWISE's scanning pattern, centered on great circles around the Sun, systematically misses objects that flash once and fade, or change gradually over years. No fully automated catalog based on NEOWISE alone will catch every variable phenomenon. That constraint shapes what Paz's 1.5 million candidates actually represent.

The Technical Accomplishment

VARnet processes astronomical time-series data through three integrated stages: wavelet decomposition reduces spurious measurements, a modified discrete Fourier transform extracts periodic features from irregularly sampled light curves, and a convolutional neural network classifies each source into four categories—non-variable, transient events like supernovae, intrinsic pulsators, or eclipsing binaries.

The model runs at less than 53 microseconds per source on a GPU with 22 gigabytes of VRAM, achieving an F1 score of 0.91 on validation data of known variables. That efficiency matters because it scales: Paz's approach can process the entire NEOWISE dataset, something that would have taken conventional methods years, if they could work at all. The Astronomical Journal published the complete technical specifications in peer review, legitimizing both the method and the teenager who built it.

What Comes Next

The 1.5 million flagged sources are candidates, not confirmations. Some will be known objects characterized in infrared wavelengths for the first time. Some will be false positives. Some fraction—the size of which remains unknown—will be genuine discoveries of quasars, variable stars, and transient events requiring follow-up observation. The full catalog is scheduled for release in 2025, providing the astronomical community a dataset large enough to support statistical studies of infrared variability across the entire sky rather than piecemeal analyses. Paz, now a Caltech employee at IPAC while finishing high school, has already begun discussing potential applications beyond astronomy—time-series analysis in financial markets, atmospheric pollution tracking, and other fields where periodic patterns matter. The teenager who walked into a lab with ambition just handed astronomers a decade's worth of new work.

💡
Think of it like...

VARnet processes data at 53 microseconds per star—fast enough to analyze 200 billion detections from a decade of observations. That's equivalent to sorting through 20 libraries' worth of books in the time it takes you to blink.

Related Entities

Matteo Paz·person
Davy Kirkpatrick·person
Caltech·facility
IPAC·facility
NASA·agency
NEOWISE·satellite
WISE·satellite
Shoubaneh Hemmati·person
Daniel Masters·person
Ashish Mahabal·person
Matthew Graham·person
Pasadena High School·facility
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Space Weather4 days ago

ESA captures 'ring of fire' eclipse from space in ultraviolet light

ESA's Proba-2 Captures Rare Annular Eclipse From Above Atmosphere On February 17, 2026, the European Space Agency's Proba-2 satellite achieved what ground-based observatories cannot: a crisp, unobstructed view of an annular solar eclipse from space. The spacecraft captured the event in extreme ultraviolet light, revealing the Sun's corona—its wispy, million-degree outer atmosphere—with unprecedented clarity. Unlike observers on Earth, who watched the Moon form a brilliant "ring of fire" across the Sun's disk, Proba-2 documented the eclipse free from atmospheric distortion, providing scientists with raw data on solar behavior that could reshape how we prepare for space weather threats to critical infrastructure. An annular eclipse occurs when the Moon passes directly between Earth and Sun but appears too small to completely block our star. This happens because the Moon sits farther along its elliptical orbit, making it smaller in the sky than the Sun. The result is a glowing ring—the photosphere—visible around the Moon's silhouette. While dramatic from Earth, the real scientific payoff comes from space. Proba-2's SWAP (Sun Watcher using Active Pixel System) imager operates at 17.4 nanometers, a wavelength that penetrates the Sun's corona to reveal solar flares and coronal mass ejections in detail. Ground-based telescopes cannot access this information because Earth's atmosphere absorbs ultraviolet light. Why This Matters Now The timing of Proba-2's observations arrives as space agencies worldwide confront an uncomfortable reality: we are ill-equipped for the next major solar storm. In May 2024, a geomagnetic storm rated G4 (severe) disrupted farming equipment GPS across North America and degraded power grid stability. Scientists warn that a Carrington Event-scale storm—possible within the next 12 years—could cause trillions in economic damage. By monitoring the Sun's corona during eclipses, researchers can refine models that predict when and where coronal mass ejections will hit Earth. Proba-2's 2026 data feeds directly into this effort. Proba-2, launched in 2009, represents a lean approach to solar science. The satellite is small—fitting inside a compact spacecraft architecture—yet bristles with sophisticated instrumentation. Its longevity (now in its 15th year of operation) reflects solid engineering and ESA's commitment to sustained solar monitoring. The SWAP imager has been the backbone of ultraviolet solar research for over a decade, making the February 2026 eclipse observations a natural extension of an already robust mission. The Broader Context Solar eclipse observations from space have accelerated scientific discovery since NASA's Skylab era in the 1970s. Modern satellites like Proba-2, SDO (Solar Dynamics Observatory), and Japan's Hinode have transformed our understanding of solar dynamics. The February 2026 eclipse is part of a constellation of upcoming celestial events: a total solar eclipse crosses Greenland, Iceland, and Spain on August 12, 2026, followed by another total eclipse over North Africa and the Middle East on August 2, 2027. Each event offers opportunities for both space-based and terrestrial science campaigns. What's Next The data Proba-2 collected during the February 2026 annular eclipse will be processed and released to the broader scientific community, likely yielding dozens of peer-reviewed papers on solar corona dynamics and heating mechanisms. Meanwhile, space agencies are preparing deployment of next-generation solar observatories—including ESA's upcoming Solar Orbiter deep-dive missions and NASA's planned solar probe fleet—designed to get even closer to the Sun and capture phenomena invisible to current instruments. The 2026 eclipse serves as both a capstone to a generation of solar science and a proving ground for the observational strategies that will guide the next decade of heliophysics research.

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