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By NASA
NASA/Kim Shiflett The Artemis II crew (from front left to back right) – pilot Victor Glover, commander Reid Wiseman, mission specialist Jeremy Hansen of CSA (Canadian Space Agency), and mission specialist Christina Koch – walk out of the Neil A. Armstrong Operations and Checkout Building at NASA’s Kennedy Space Center in Florida on Monday, Aug. 11, 2025.
During a two-day training, the crew practiced launch day operations if the Artemis II test flight launches at night.
Join the Artemis II mission and sign up to launch your name aboard the Orion spacecraft and SLS (Space Launch System) rocket alongside the crew.
Through the Artemis program, NASA will send astronauts to explore the Moon for scientific discovery, economic benefits, and to build the foundation for the first crewed missions to Mars – for the benefit of all.
Image credit: NASA/Kim Shiflett
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By NASA
Explore Hubble Science Hubble Space Telescope As NASA Missions Study… Hubble Home Overview About Hubble The History of Hubble Hubble Timeline Why Have a Telescope in Space? Hubble by the Numbers At the Museum FAQs Impact & Benefits Hubble’s Impact & Benefits Science Impacts Cultural Impact Technology Benefits Impact on Human Spaceflight Astro Community Impacts Science Hubble Science Science Themes Science Highlights Science Behind Discoveries Hubble’s Partners in Science Universe Uncovered AI and Hubble Science Explore the Night Sky Observatory Hubble Observatory Hubble Design Mission Operations Missions to Hubble Hubble vs Webb Team Hubble Team Career Aspirations Hubble Astronauts Multimedia Images Videos Sonifications Podcasts e-Books Online Activities 3D Hubble Models Lithographs Fact Sheets Posters Hubble on the NASA App Glossary News Hubble News Social Media Media Resources More 35th Anniversary Online Activities 4 min read
As NASA Missions Study Interstellar Comet, Hubble Makes Size Estimate
Hubble captured this image of the interstellar comet 3I/ATLAS on July 21, 2025, when the comet was 277 million miles from Earth. Hubble shows that the comet has a teardrop-shaped cocoon of dust coming off its solid, icy nucleus. Image: NASA, ESA, David Jewitt (UCLA); Image Processing: Joseph DePasquale (STScI) A team of astronomers has taken the sharpest-ever picture of the unexpected interstellar comet 3I/ATLAS using the crisp vision of NASA’s Hubble Space Telescope. Hubble is one of many missions across NASA’s fleet of space telescopes slated to observe this comet, together providing more information about its size and physical properties. While the comet poses no threat to Earth, NASA’s space telescopes help support the agency’s ongoing mission to find, track, and better understand near-Earth objects.
Hubble’s observations allow astronomers to more accurately estimate the size of the comet’s solid, icy nucleus. The upper limit on the diameter of the nucleus is 3.5 miles (5.6 kilometers), though it could be as small as 1,000 feet (320 meters) across, researchers report. Though the Hubble images put tighter constraints on the size of the nucleus compared to previous ground-based estimates, the solid heart of the comet presently cannot be directly seen, even by Hubble. Observations from other NASA missions including the James Webb Space Telescope, TESS (Transiting Exoplanet Survey Satellite), and the Neil Gehrels Swift Observatory, as well as NASA’s partnership with the W.M. Keck Observatory, will help further refine our knowledge about the comet, including its chemical makeup.
Hubble also captured a dust plume ejected from the Sun-warmed side of the comet, and the hint of a dust tail streaming away from the nucleus. Hubble’s data yields a dust-loss rate consistent with comets that are first detected around 300 million miles from the Sun. This behavior is much like the signature of previously seen Sun-bound comets originating within our solar system.
The big difference is that this interstellar visitor originated in some other solar system elsewhere in our Milky Way galaxy.
3I/ATLAS is traveling through our solar system at a staggering 130,000 miles (209,000 kilometers) per hour, the highest velocity ever recorded for a solar system visitor. This breathtaking sprint is evidence that the comet has been drifting through interstellar space for many billions of years. The gravitational slingshot effect from innumerable stars and nebulae the comet passed added momentum, ratcheting up its speed. The longer 3I/ATLAS was out in space, the higher its speed grew.
“No one knows where the comet came from. It’s like glimpsing a rifle bullet for a thousandth of a second. You can’t project that back with any accuracy to figure out where it started on its path,” said David Jewitt of the University of California, Los Angeles, science team leader for the Hubble observations.
The paper will be published in The Astrophysical Journal Letters. It is already available on Astro-ph.
New Evidence for Population of Wandering Space Relics
“This latest interstellar tourist is one of a previously undetected population of objects bursting onto the scene that will gradually emerge,” said Jewitt. “This is now possible because we have powerful sky survey capabilities that we didn’t have before. We’ve crossed a threshold.”
This comet was discovered by the NASA-funded Asteroid Terrestrial-impact Last Alert System (ATLAS) on July 1, 2025, at a distance of 420 million miles from the Sun. ATLAS is an asteroid impact early warning system developed by the University of Hawai’i.
In the meantime, other NASA missions will provide new insight into this third interstellar interloper, helping refine our understanding of these objects for the benefit of all. 3I/ATLAS should remain visible to ground-based telescopes through September, after which it will pass too close to the Sun to observe, and is expected to reappear on the other side of the Sun by early December.
The Hubble Space Telescope has been operating for more than three decades and continues to make ground-breaking discoveries that shape our fundamental understanding of the universe. Hubble is a project of international cooperation between NASA and ESA (European Space Agency). NASA’s Goddard Space Flight Center in Greenbelt, Maryland, manages the telescope and mission operations. Lockheed Martin Space, based in Denver, also supports mission operations at Goddard. The Space Telescope Science Institute in Baltimore, which is operated by the Association of Universities for Research in Astronomy, conducts Hubble science operations for NASA.
To learn more about Hubble, visit: https://science.nasa.gov/hubble
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Comet 3I/ATLAS
Hubble captured this image of the interstellar comet 3I/ATLAS on July 21, 2025, when the comet was 277 million miles from Earth. Hubble shows that the comet has a teardrop-shaped cocoon of dust coming off its solid, icy nucleus.
Comet 3I/ATLAS Compass Image
This image of interstellar comet 3I/ATLAS was captured by the Hubble Space Telescope’s Wide Field Camera on July 21, 2025. The scale bar is labeled in arcseconds, which is a measure of angular distance on the sky. One arcsecond is equal an angular measurement of 1/3600 of o…
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Last Updated Aug 07, 2025 Editor Andrea Gianopoulos Location NASA Goddard Space Flight Center Contact Media Claire Andreoli
NASA’s Goddard Space Flight Center
Greenbelt, Maryland
claire.andreoli@nasa.gov
Ray Villard
Space Telescope Science Institute
Baltimore, Maryland
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Hubble Space Telescope Astrophysics Astrophysics Division Comets Goddard Space Flight Center Small Bodies of the Solar System The Solar System
Related Links and Documents
Science Paper: Hubble Space Telescope Observations of the Interstellar Interloper 3I/ATLAS, PDF (1.57 MB)
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Since its 1990 launch, the Hubble Space Telescope has changed our fundamental understanding of the universe.
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By NASA
NASA/Carla Thomas NASA’s X-59 quiet supersonic research aircraft completed its first low-speed taxi test at U.S. Air Force Plant 42 in Palmdale, California, on July 10, 2025. This marked the first time the one-of-a-kind experimental aircraft has ever moved under its own power.
During the test, engineers and flight crews monitored the X-59 as it moved across the runway, working to validate critical systems like steering and braking. The taxiing represents the start of the X-59’s final series of ground tests before first flight.
The X-59 is the centerpiece of NASA’s Quesst mission, which aims to demonstrate quiet supersonic flight by reducing the loud sonic boom to a quieter “thump.”
Image Credit: NASA/Carla Thomas
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By Space Force
Colorado Springs is playing host to the DOD Warrior Games July 18-26, and for the first time, Guardians are among the nearly 200 wounded, ill and injured athletes competing in 11 adaptive sports over nine days.
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By NASA
6 min read
Smarter Searching: NASA AI Makes Science Data Easier to Find
Image snapshot taken from NASA Worldview of NASA’s Global Precipitation Measurement (GPM) mission on March 15, 2025 showing heavy rain across the southeastern U.S. with an overlay of the GCMD Keyword Recommender for Earth Science, Atmosphere, Precipitation, Droplet Size. NASA Worldview Imagine shopping for a new pair of running shoes online. If each seller described them differently—one calling them “sneakers,” another “trainers,” and someone else “footwear for exercise”—you’d quickly feel lost in a sea of mismatched terminology. Fortunately, most online stores use standardized categories and filters, so you can click through a simple path: Women’s > Shoes > Running Shoes—and quickly find what you need.
Now, scale that problem to scientific research. Instead of sneakers, think “aerosol optical depth” or “sea surface temperature.” Instead of a handful of retailers, it is thousands of researchers, instruments, and data providers. Without a common language for describing data, finding relevant Earth science datasets would be like trying to locate a needle in a haystack, blindfolded.
That’s why NASA created the Global Change Master Directory (GCMD), a standardized vocabulary that helps scientists tag their datasets in a consistent and searchable way. But as science evolves, so does the challenge of keeping metadata organized and discoverable.
To meet that challenge, NASA’s Office of Data Science and Informatics (ODSI) at the agency’s Marshall Space Flight Center (MSFC) in Huntsville, Alabama, developed the GCMD Keyword Recommender (GKR): a smart tool designed to help data providers and curators assign the right keywords, automatically.
Smarter Tagging, Accelerated Discovery
The upgraded GKR model isn’t just a technical improvement; it’s a leap forward in how we organize and access scientific knowledge. By automatically recommending precise, standardized keywords, the model reduces the burden on human curators while ensuring metadata quality remains high. This makes it easier for researchers, students, and the public to find exactly the datasets they need.
It also sets the stage for broader applications. The techniques used in GKR, like applying focal loss to rare-label classification problems and adapting pre-trained transformers to specialized domains, can benefit fields well beyond Earth science.
Metadata Matchmaker
The newly upgraded GKR model tackles a massive challenge in information science known as extreme multi-label classification. That’s a mouthful, but the concept is straightforward: Instead of predicting just one label, the model must choose many, sometimes dozens, from a set of thousands. Each dataset may need to be tagged with multiple, nuanced descriptors pulled from a controlled vocabulary.
Think of it like trying to identify all the animals in a photograph. If there’s just a dog, it’s easy. But if there’s a dog, a bird, a raccoon hiding behind a bush, and a unicorn that only shows up in 0.1% of your training photos, the task becomes far more difficult. That’s what GKR is up against: tagging complex datasets with precision, even when examples of some keywords are scarce.
And the problem is only growing. The new version of GKR now considers more than 3,200 keywords, up from about 430 in its earlier iteration. That’s a sevenfold increase in vocabulary complexity, and a major leap in what the model needs to learn and predict.
To handle this scale, the GKR team didn’t just add more data; they built a more capable model from the ground up. At the heart of the upgrade is INDUS, an advanced language model trained on a staggering 66 billion words drawn from scientific literature across disciplines—Earth science, biological sciences, astronomy, and more.
NASA ODSI’s GCMD Keyword Recommender AI model automatically tags scientific datasets with the help of INDUS, a large language model trained on NASA scientific publications across the disciplines of astrophysics, biological and physical sciences, Earth science, heliophysics, and planetary science. NASA “We’re at the frontier of cutting-edge artificial intelligence and machine learning for science,” said Sajil Awale, a member of the NASA ODSI AI team at MSFC. “This problem domain is interesting, and challenging, because it’s an extreme classification problem where the model needs to differentiate even very similar keywords/tags based on small variations of context. It’s exciting to see how we have leveraged INDUS to build this GKR model because it is designed and trained for scientific domains. There are opportunities to improve INDUS for future uses.”
This means that the new GKR isn’t just guessing based on word similarities; it understands the context in which keywords appear. It’s the difference between a model knowing that “precipitation” might relate to weather versus recognizing when it means a climate variable in satellite data.
And while the older model was trained on only 2,000 metadata records, the new version had access to a much richer dataset of more than 43,000 records from NASA’s Common Metadata Repository. That increased exposure helps the model make more accurate predictions.
The Common Metadata Repository is the backend behind the following data search and discovery services:
Earthdata Search International Data Network Learning to Love Rare Words
One of the biggest hurdles in a task like this is class imbalance. Some keywords appear frequently; others might show up just a handful of times. Traditional machine learning approaches, like cross-entropy loss, which was used initially to train the model, tend to favor the easy, common labels, and neglect the rare ones.
To solve this, NASA’s team turned to focal loss, a strategy that reduces the model’s attention to obvious examples and shifts focus toward the harder, underrepresented cases.
The result? A model that performs better across the board, especially on the keywords that matter most to specialists searching for niche datasets.
From Metadata to Mission
Ultimately, science depends not only on collecting data, but on making that data usable and discoverable. The updated GKR tool is a quiet but critical part of that mission. By bringing powerful AI to the task of metadata tagging, it helps ensure that the flood of Earth observation data pouring in from satellites and instruments around the globe doesn’t get lost in translation.
In a world awash with data, tools like GKR help researchers find the signal in the noise and turn information into insight.
Beyond powering GKR, the INDUS large language model is also enabling innovation across other NASA SMD projects. For example, INDUS supports the Science Discovery Engine by helping automate metadata curation and improving the relevancy ranking of search results.The diverse applications reflect INDUS’s growing role as a foundational AI capability for SMD.
The INDUS large language model is funded by the Office of the Chief Science Data Officer within NASA’s Science Mission Directorate at NASA Headquarters in Washington. The Office of the Chief Science Data Officer advances scientific discovery through innovative applications and partnerships in data science, advanced analytics, and artificial intelligence.
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Last Updated Jul 09, 2025 Related Terms
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