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CubeSat will sift asteroid secrets from reflected sunshine
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By NASA
The IAU (International Astronomical Union), an international non-governmental research organization and global naming authority for celestial objects, has approved official names for features on Donaldjohanson, an asteroid NASA’s Lucy spacecraft visited on April 20. In a nod to the fossilized inspiration for the names of the asteroid and spacecraft, the IAU’s selections recognize significant sites and discoveries on Earth that further our understanding of humanity’s origins.
The asteroid was named in 2015 after paleoanthropologist Donald Johanson, discoverer of one of the most famous fossils ever found of a female hominin, or ancient human ancestor, nicknamed Lucy. Just as the Lucy fossil revolutionized our understanding of human evolution, NASA’s Lucy mission aims to revolutionize our understanding of solar system evolution by studying at least eight Trojan asteroids that share an orbit with Jupiter.
Postcard commemorating NASA’s Lucy spacecraft April 20, 2025, encounter with the asteroid Donaldjohanson. NASA’s Goddard Space Flight Center Donaldjohanson, located in the main asteroid belt between the orbits of Mars and Jupiter, was a target for Lucy because it offered an opportunity for a comprehensive “dress rehearsal” for Lucy’s main mission, with all three of its science instruments carrying out observation sequences very similar to the ones that will occur at the Trojans.
After exploring the asteroid and getting to see its features up close, the Lucy science and engineering team proposed to name the asteroid’s surface features in recognition of significant paleoanthropological sites and discoveries, which the IAU accepted.
The smaller lobe is called Afar Lobus, after the Ethiopian region where Lucy and other hominin fossils were found. The larger lobe is named Olduvai Lobus, after the Tanzanian river gorge that has also yielded many important hominin discoveries.
The asteroid’s neck, Windover Collum, which joins those two lobes, is named after the Windover Archeological Site near Cape Canaveral Space Force Station in Florida — where NASA’s Lucy mission launched in 2021. Human remains and artifacts recovered from that site revolutionized our understanding of the people who lived in Florida around 7,300 years ago.
Officially recognized names of geologic features on the asteroid Donaldjohanson. NASA Goddard/SwRI/Johns Hopkins APL Two smooth areas on the asteroid’s neck are named Hadar Regio, marking the specific site of Johanson’s discovery of the Lucy fossil, and Minatogawa Regio, after the location where the oldest known hominins in Japan were found. Select boulders and craters on Donaldjohanson are named after notable fossils ranging from pre-Homo sapiens hominins to ancient modern humans. The IAU also approved a coordinate system for mapping features on this uniquely shaped small world.
As of Sept. 9, the Lucy spacecraft was nearly 300 million miles (480 million km) from the Sun en route to its August 2027 encounter with its first Trojan asteroid called Eurybates. This places Lucy about three quarters of the way through the main asteroid belt. Since its encounter with Donaldjohanson, Lucy has been cruising without passing close to any other asteroids, and without requiring any trajectory correction maneuvers.
The team continues to carefully monitor the instruments and spacecraft as it travels farther from the Sun into a cooler environment.
Stay tuned at nasa.gov/lucy for more updates as Lucy continues its journey toward the never-before-explored Jupiter Trojan asteroids.
By Katherine Kretke
Southwest Research Institute
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By NASA
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NASA, IBM’s ‘Hot’ New AI Model Unlocks Secrets of Sun
This image from June 20, 2013 shows the bright light of a solar flare and an eruption of solar material shooting through the sun’s atmosphere, called a prominence eruption. Shortly thereafter, this same region of the sun sent a coronal mass ejection out into space — a phenomenon which can cause magnetic storms that degrade communication signals and cause unexpected electrical surges in power grids on Earth. NASA’s new heliophysics AI foundation model, Surya, can help predict these storms. NASA/Goddard/SDO NASA is turning up the heat in solar science with the launch of the Surya Heliophysics Foundational Model, an artificial intelligence (AI) model trained on 14 years of observations from NASA’s Solar Dynamics Observatory.
Developed by NASA in partnership with IBM and others, Surya uses advances in AI to analyze vast amounts of solar data, helping scientists better understand solar eruptions and predict space weather that threatens satellites, power grids, and communication systems. The model can be used to provide early warnings to satellite operators and helps scientists predict how the Sun’s ultraviolet output affects Earth’s upper atmosphere.
Preliminary results show Surya is making strides in solar flare forecasting, a long-standing challenge in heliophysics. Surya, with its ability to generate visual predictions of solar flares two hours into the future, marks a major step towards the use of AI for operational space weather prediction. These initial results surpass existing benchmarks by 15%. By providing open access to the model on HuggingFace and the code on GitHub, NASA encourages the science and applications community to test and explore this AI model for innovative solutions that leverage the unique value of continuous, stable, long-duration datasets from the Solar Dynamics Observatory.
Illustrations of Solar Dynamics Observatory solar imagery used for training Surya: Solar coronal ultraviolet and extreme ultraviolet images from the Atmospheric Imaging Assembly (AIA) and solar surface velocity and magnetic field maps from the Helioseismic and Magnetic Imager (HMI). NASA/SDO The model’s success builds directly on the Solar Dynamics Observatory’s long-term database. Launched in 2010, NASA’s Solar Dynamics Observatory has provided an unbroken, high-resolution record of the Sun for nearly 15 years through capturing images every 12 seconds in multiple wavelengths, plus precise magnetic field measurements. This stable, well-calibrated dataset, spanning an entire solar cycle, is uniquely suited for training AI models like Surya, enabling them to detect subtle patterns in solar behavior that shorter datasets would miss.
Surya’s strength lies in its foundation model architecture, which learns directly from raw solar data. Unlike traditional AI systems that require extensive labeling, Surya can adapt quickly to new tasks and applications. Applications include tracking active regions, forecasting flare activity, predicting solar wind speed, and integrating data from other observatories including the joint NASA-ESA Solar and Heliospheric Observatory mission and NASA’s Parker Solar Probe.
“We are advancing data-driven science by embedding NASA’s deep scientific expertise into cutting-edge AI models,” said Kevin Murphy, chief science data officer at NASA Headquarters in Washington. “By developing a foundation model trained on NASA’s heliophysics data, we’re making it easier to analyze the complexities of the Sun’s behavior with unprecedented speed and precision. This model empowers broader understanding of how solar activity impacts critical systems and technologies that we all rely on here on Earth.”
These images compare the ground-truth data (right) with model output (center) for solar flares, which are the events behind most space weather. Surya’s prediction is very close to what happened in reality (right). These preliminary results suggest that Surya has learned enough solar physics to predict the structure and evolution of a solar flare by looking at its beginning phase. NASA/SDO/ODSI IMPACT AI Team Solar storms pose significant risks to our technology-dependent society. Powerful solar events energize Earth’s ionosphere, resulting in substantial GPS errors or complete signal loss to satellite communications. They also pose risks to power grids, as geomagnetically induced currents from coronal mass ejections can overload transformers and trigger widespread outages.
In commercial aviation, solar flares can disrupt radio communications and navigation systems while exposing high-altitude flights to increased radiation. The stakes are even higher for human spaceflight. Astronauts bound for the Moon or Mars may need to depend on precise predictions to shelter from intense radiation during solar particle events.
The Sun’s influence extends to the growing number of low Earth orbit satellites, including those that deliver global high-speed internet. As solar activity intensifies, it heats Earth’s upper atmosphere, increasing drag that slows satellites, pulls them from orbit, and causes premature reentry. Satellite operators often struggle to forecast where and when solar flares might affect these satellites.
The “ground truth” solar activity is shown on the top row. The bottom row shows solar activity predicted by Surya. NASA/SDO/ODSI IMPACT AI Team “Our society is built on technologies that are highly susceptible to space weather,” said Joseph Westlake, Heliophysics Division director at NASA Headquarters. “Just as we use meteorology to forecast Earth’s weather, space weather forecasts predict the conditions and events in the space environment that can affect Earth and our technologies. Applying AI to data from our heliophysics missions is a vital step in increasing our space weather defense to protect astronauts and spacecraft, power grids and GPS, and many other systems that power our modern world.”
While Surya is designed to study the Sun, its architecture and methodology are adaptable across scientific domains. From planetary science to Earth observation, the project lays the foundational infrastructure for similar AI efforts in diverse domains.
Surya is part of a broader NASA push to develop open-access, AI-powered science tools. Both the model and training datasets are freely available online to researchers, educators, and students worldwide, lowering barriers to participation and sparking new discoveries.
The process for creating Surya. Foundation models enhance the utility of NASA’s Solar Dynamics Observatory datasets and create a base for building new applications. NASA/ODSI IMPACT AI Team Surya’s training was supported in part by the National Artificial Intelligence Research Resource (NAIRR) Pilot, a National Science Foundation (NSF)-led initiative that provides researchers with access to advanced computing, datasets, and AI tools. The NAIRR Pilot brings together federal and industry resources, such as computing power from NVIDIA, to expand access to the infrastructure needed for cutting-edge AI research.
“This project shows how the NAIRR Pilot is uniting federal and industry AI resources to accelerate scientific breakthroughs,” said Katie Antypas, director of NSF’s Office of Advanced Cyberinfrastructure. “With support from NVIDIA and NSF, we’re not only enabling today’s research, we’re laying the groundwork for a national AI network to drive tomorrow’s discoveries.”
Surya is part of a larger effort championed and supported by NASA’s Office of the Chief Science Data Officer and Heliophysics Division, the NSF , and partnering universities to advance NASA’s scientific missions through innovative data science and AI models. Surya’s AI architecture was jointly developed by the Interagency Implementation and Advanced Concepts Team (IMPACT) under the Office of Data Science and Informatics at NASA’s Marshall Space Flight Center in Huntsville, Alabama; IBM; and a collaborative science team.
The science team, assembled by NASA Headquarters, consisted of experts from the Southwest Research Institute in San Antonio, Texas; the University of Alabama in Huntsville in Huntsville, Alabama; the University of Colorado Boulder in Boulder, Colorado; Georgia State University in Atlanta, Georgia; Princeton University in Princeton, New Jersey; NASA’s SMD’s Heliophysics Division; NASA’s Goddard Space Flight Center in Greenbelt, Maryland; NASA’s Jet Propulsion Laboratory in Pasadena, California; and the SETI Institute in Mountain View, California.
For a behind-the-scenes dive into Surya’s architecture, industry and academic collaborations, challenges behind developing the model, read the blog post on NASA’s Science Data Portal:
https://science.data.nasa.gov/features-events/inside-surya-solar-ai-model
For more information about NASA’s strategy of developing foundation models for science, visit:
https://science.nasa.gov/artificial-intelligence-science
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Last Updated Aug 20, 2025 Related Terms
Science & Research Artificial Intelligence (AI) Heliophysics Solar Dynamics Observatory (SDO) The Sun The Sun & Solar Physics Explore More
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Hera is currently travelling through space on its way to a binary asteroid system. In 2022, NASA’s DART spacecraft impacted the asteroid Dimorphos, changing its orbit around the larger asteroid Didymos. Now, Hera is returning to the system to help turn asteroid deflection into a reliable technique for planetary defence.
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By European Space Agency
Asteroid 2024 YR4 made headlines earlier this year when its probability of impacting Earth in 2032 rose as high as 3%. While an Earth impact has now been ruled out, the asteroid’s story continues.
The final glimpse of the asteroid as it faded out of view of humankind’s most powerful telescopes left it with a 4% chance of colliding with the Moon on 22 December 2032.
The likelihood of a lunar impact will now remain stable until the asteroid returns to view in mid-2028. In this FAQ, find out why we are left with this lingering uncertainty and how ESA's planned NEOMIR space telescope will help us avoid similar situations in the future.
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By European Space Agency
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