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Juice’s journey and Jupiter system tour
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By NASA
NASA, ESA, and M. Wong (University of California – Berkeley); Processing: Gladys Kober (NASA/Catholic University of America) This NASA Hubble Space Telescope image shows the planet Jupiter in a color composite of ultraviolet wavelengths. Released on Nov. 3, 2023, in honor of Jupiter reaching opposition, which occurs when the planet and the Sun are in opposite sides of the sky, this view of the gas giant planet includes the iconic, massive storm called the “Great Red Spot.” Though the storm appears red to the human eye, in this ultraviolet image it appears darker because high altitude haze particles absorb light at these wavelengths. The reddish, wavy polar hazes are absorbing slightly less of this light due to differences in either particle size, composition, or altitude.
Learn more about Hubble and how this type of data can help us learn more about our universe.
Image credit: NASA, ESA, and M. Wong (University of California – Berkeley); Processing: Gladys Kober (NASA/Catholic University of America)
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By NASA
Webb Webb News Latest News Latest Images Blog (offsite) Awards X (offsite – login reqd) Instagram (offsite – login reqd) Facebook (offsite- login reqd) Youtube (offsite) Overview About Who is James Webb? Fact Sheet Impacts+Benefits FAQ Science Overview and Goals Early Universe Galaxies Over Time Star Lifecycle Other Worlds Observatory Overview Launch Orbit Mirrors Sunshield Instrument: NIRCam Instrument: MIRI Instrument: NIRSpec Instrument: FGS/NIRISS Optical Telescope Element Backplane Spacecraft Bus Instrument Module Multimedia About Webb Images Images Videos What is Webb Observing? 3d Webb in 3d Solar System Podcasts Webb Image Sonifications Team International Team People Of Webb More For the Media For Scientists For Educators For Fun/Learning 6 Min Read Webb Watches Carbon-Rich Dust Shells Form, Expand in Star System
A portion of Webb’s 2023 observation of Wolf-Rayet 140. Credits:
Image: NASA, ESA, CSA, STScI; Science: Emma Lieb (University of Denver), Ryan Lau (NSF NOIRLab), Jennifer Hoffman (University of Denver) Astronomers have long tried to track down how elements like carbon, which is essential for life, become widely distributed across the universe. Now, NASA’s James Webb Space Telescope has examined one ongoing source of carbon-rich dust in our own Milky Way galaxy in greater detail: Wolf-Rayet 140, a system of two massive stars that follow a tight, elongated orbit.
As they swing past one another (within the central white dot in the Webb images), the stellar winds from each star slam together, the material compresses, and carbon-rich dust forms. Webb’s latest observations show 17 dust shells shining in mid-infrared light that are expanding at regular intervals into the surrounding space.
Image A: Compare Observations of Wolf-Rayet 140 (MIRI Images)
Two mid-infrared images from NASA’s James Webb Space Telescope of Wolf-Rayet 140 show carbon-rich dust moving in space. At right, the two triangles from the main images are matched up to show how much difference 14 months makes: The dust is racing away from the central stars at almost 1% the speed of light. These stars are 5,000 light-years away in our own Milky Way galaxy. Image: NASA, ESA, CSA, STScI; Science: Emma Lieb (University of Denver), Ryan Lau (NSF NOIRLab), Jennifer Hoffman (University of Denver) “The telescope not only confirmed that these dust shells are real, its data also showed that the dust shells are moving outward at consistent velocities, revealing visible changes over incredibly short periods of time,” said Emma Lieb, the lead author of the new paper and a doctoral student at the University of Denver in Colorado.
Every shell is racing away from the stars at more than 1,600 miles per second (2,600 kilometers per second), almost 1% the speed of light. “We are used to thinking about events in space taking place slowly, over millions or billions of years,” added Jennifer Hoffman, a co-author and a professor at the University of Denver. “In this system, the observatory is showing that the dust shells are expanding from one year to the next.”
Like clockwork, the stars’ winds generate dust for several months every eight years, as the pair make their closest approach during a wide, elongated orbit. Webb also shows how dust formation varies — look for the darker region at top left in both images.
Video A: Fade Between 2022 and 2023 Observations of Wolf-Rayet 140
This video alternates between two mid-infrared light observations from NASA’s James Webb Space Telescope of Wolf-Rayet 140. Over only 14 months, Webb showed the dust in the system has expanded. This two-star system has sent out more than 17 shells of dust over 130 years. Video: NASA, ESA, CSA, STScI.; Science: Emma Lieb (University of Denver), Ryan Lau (NSF NOIRLab), Jennifer Hoffman (University of Denver) Video B: Stars’ Orbits in Wolf-Rayet 140 (Visualization)
When the two massive stars in Wolf-Rayet 140 swing past one another, their winds collide, material compresses, and carbon-rich dust forms. The stronger winds of the hotter star in the Wolf-Rayet system blow behind its slightly cooler (but still hot) companion. The stars create dust for several months in every eight-year orbit.
Video: NASA, ESA, CSA, Joseph Olmsted (STScI). The telescope’s mid-infrared images detected shells that have persisted for more than 130 years. (Older shells have dissipated enough that they are now too dim to detect.) The researchers speculate that the stars will ultimately generate tens of thousands of dust shells over hundreds of thousands of years.
“Mid-infrared observations are absolutely crucial for this analysis, since the dust in this system is fairly cool. Near-infrared and visible light would only show the shells that are closest to the star,” explained Ryan Lau, a co-author and astronomer at NSF NOIRLab in Tuscon, Arizona, who led the initial research about this system. “With these incredible new details, the telescope is also allowing us to study exactly when the stars are forming dust — almost to the day.”
The dust’s distribution isn’t uniform. Though this isn’t obvious at first glance, zooming in on the shells in Webb’s images reveals that some of the dust has “piled up,” forming amorphous, delicate clouds that are as large as our entire solar system. Many other individual dust particles float freely. Every speck is as small as one-hundredth the width of a human hair. Clumpy or not, all of the dust moves at the same speed and is carbon rich.
The Future of This System
What will happen to these stars over millions or billions of years, after they are finished “spraying” their surroundings with dust? The Wolf-Rayet star in this system is 10 times more massive than the Sun and nearing the end of its life. In its final “act,” this star will either explode as a supernova — possibly blasting away some or all of the dust shells — or collapse into a black hole, which would leave the dust shells intact.
Though no one can predict with any certainty what will happen, researchers are rooting for the black hole scenario. “A major question in astronomy is, where does all the dust in the universe come from?” Lau said. “If carbon-rich dust like this survives, it could help us begin to answer that question.”
“We know carbon is necessary for the formation of rocky planets and solar systems like ours,” Hoffman added. “It’s exciting to get a glimpse into how binary star systems not only create carbon-rich dust, but also propel it into our galactic neighborhood.”
These results have been published in the Astrophysical Journal Letters and were presented in a press conference at the 245th meeting of the American Astronomical Society in National Harbor, Maryland.
The James Webb Space Telescope is the world’s premier space science observatory. Webb will solve mysteries in our solar system, look beyond to distant worlds around other stars, and probe the mysterious structures and origins of our universe and our place in it. Webb is an international program led by NASA with its partners, ESA (European Space Agency) and the Canadian Space Agency.
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Media Contacts
Laura Betz – laura.e.betz@nasa.gov
NASA’s Goddard Space Flight Center, Greenbelt, Md.
Claire Blome – cblome@stsci.edu, Christine Pulliam – cpulliam@stsci.edu
Space Telescope Science Institute, Baltimore, Md.
Science – Emma Lieb (University of Denver)
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Last Updated Jan 13, 2025 Editor Marty McCoy Contact Laura Betz laura.e.betz@nasa.gov Related Terms
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By NASA
On Jan. 7, 1610, Italian astronomer Galileo Galilei peered through his newly improved 20-power homemade telescope at the planet Jupiter. He noticed three other points of light near the planet, at first believing them to be distant stars. Observing them over several nights, he noted that they appeared to move in the wrong direction with regard to the background stars and they remained in Jupiter’s proximity but changed their positions relative to one another. Four days later, he observed a fourth point of light near the planet with the same unusual behavior. By Jan. 15, Galileo correctly concluded that he had discovered four moons orbiting around Jupiter, providing strong evidence for the Copernican theory that most celestial objects did not revolve around the Earth.
Two of Galileo’s telescopes.National Geographic. Painting by Giuseppe Bertini (1858) of Galileo demonstrating his telescope to the Doge of Venice.gabrielevanin.it Page from Galileo’s notebook about his observations of Jupiter’s satellites.University of Michigan Special Collections Library. In March 1610, Galileo published his discoveries of Jupiter’s satellites and other celestial observations in a book titled Siderius Nuncius (The Starry Messenger). As their discoverer, Galileo had naming rights to Jupiter’s satellites. He proposed to name them after his patrons the Medicis and astronomers called them the Medicean Stars through much of the seventeenth century, although in his own notes Galileo referred to them by the Roman numerals I, II, III, and IV, in order of their distance from Jupiter. Astronomers still refer to the four moons as the Galilean satellites in honor of their discoverer.
In 1614, the German astronomer Johannes Kepler suggested naming the satellites after mythological figures associated with Jupiter, namely Io, Europa, Ganymede, and Callisto, but his idea didn’t catch on for more than 200 years. Scientists didn’t discover any more satellites around Jupiter until 1892 when American astronomer E.E. Barnard found Jupiter’s fifth moon Amalthea, much smaller than the Galilean moons and orbiting closer to the planet than Io. It was the last satellite in the solar system found by visual observation – all subsequent discoveries occurred via photography or digital imaging. As of today, astronomers have identified 95 moons orbiting Jupiter.
Image of Jupiter and three of its four Galilean satellites through an amateur telescope, similar to what Galileo might have seen. Hubble Space Telescope image of Jupiter and three of its four Galilean satellites during a rare triple transit. Although each of the Galilean satellites has unique features, such as the volcanoes of Io, the heavily cratered surface of Callisto, and the magnetic field of Ganymede, scientists have focused more attention on Europa due to the tantalizing possibility that it might be hospitable to life. In the 1970s, NASA’s Pioneer 10 and 11 and Voyager 1 and 2 spacecraft took ever increasingly detailed images of the large satellites including Europa during their flybys of Jupiter. The photographs revealed Europa to have the smoothest surface of any object in the solar system, indicating a relatively young crust, and also one of the brightest of any satellite indicating a highly reflective surface. These features led scientists to hypothesize that Europa is covered by an icy crust floating on a subsurface salty ocean. They further postulated that tidal heating caused by Jupiter’s gravity reforms the surface ice layer in cycles of melting and freezing.
Image of Europa taken by Pioneer 10 during its flyby of Jupiter in 1973. Image of Europa taken by Voyager 1 during its 1979 flyby of Jupiter. Image of Europa taken by Voyager 2 during its 1979 flyby of Jupiter. More detailed observations from NASA’s Galileo spacecraft that orbited Jupiter between 1995 and 2003 and completed 11 close encounters with Europa revealed that long linear features on its surface may indicate tidal or tectonic activity. Reddish-brown material along the fissures and in splotches elsewhere on the surface may contain salts and sulfur compounds transported from below the crust and modified by radiation. Observations from the Hubble Space Telescope and re-analysis of images from Galileo revealed possible plumes emanating from beneath Europa’s crust, lending credence to that hypothesis. While the exact composition of this material is not known, it likely holds clues to whether Europa may be hospitable to life.
Global view of Europa from the Galileo spacecraft. More detailed views of varied terrain on Europa from Galileo. Cutaway illustration of Europa’s icy crust, subsurface ocean and possible vents that transport material to the surface. Future robotic explorers of Europa may answer some of the outstanding questions about this unique satellite of Jupiter. NASA’s Europa Clipper set off in October 2024 on a 5.5-year journey to Jupiter. After its arrival in 2030, the spacecraft will enter orbit around the giant planet and conduct 49 flybys of Europa during its four-year mission. Managed by the Jet Propulsion Laboratory in Pasadena, California, and the Applied Physics Laboratory at Johns Hopkins University in Baltimore, Maryland, Europa Clipper will carry nine instruments including imaging systems and a radar to better understand the structure of the icy crust. Data from Europa Clipper will complement information returned by the European Space Agency’s JUICE (Jupiter Icy Moon Explorer) spacecraft. Launched in April 2023, JUICE will first enter orbit around Jupiter in 2031 and then enter orbit around Ganymede in 2034. The spacecraft also plans to conduct studies of Europa complementary with Europa Clipper’s. The two spacecraft should greatly increase our understanding of Europa and perhaps uncover new mysteries.
Illustration of the Europa Clipper spacecraft investigating Europa. Illustration of the JUICE spacecraft exploring Europa.European Space Agency. View the full article
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By Amazing Space
Winter Sky Guide: Orion, Pleiades & Jupiter Alignment | Meteor Shower Captured! Stargazing
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By NASA
Download PDF: Statistical Analysis Using Random Forest Algorithm Provides Key Insights into Parachute Energy Modulator System
Energy modulators (EM), also known as energy absorbers, are safety-critical components that are used to control shocks and impulses in a load path. EMs are textile devices typically manufactured out of nylon, Kevlar® and other materials, and control loads by breaking rows of stitches that bind a strong base webbing together as shown in Figure 1. A familiar EM application is a fall-protection harness used by workers to prevent injury from shock loads when the harness arrests a fall. EMs are also widely used in parachute systems to control shock loads experienced during the various stages of parachute system deployment.
Random forest is an innovative algorithm for data classification used in statistics and machine learning. It is an easy to use and highly flexible ensemble learning method. The random forest algorithm is capable of modeling both categorical and continuous data and can handle large datasets, making it applicable in many situations. It also makes it easy to evaluate the relative importance of variables and maintains accuracy even when a dataset has missing values.
Random forests model the relationship between a response variable and a set of predictor or independent variables by creating a collection of decision trees. Each decision tree is built from a random sample of the data. The individual trees are then combined through methods such as averaging or voting to determine the final prediction (Figure 2). A decision tree is a non-parametric supervised learning algorithm that partitions the data using a series of branching binary decisions. Decision trees inherently identify key features of the data and provide a ranking of the contribution of each feature based on when it becomes relevant. This capability can be used to determine the relative importance of the input variables (Figure 3). Decision trees are useful for exploring relationships but can have poor accuracy unless they are combined into random forests or other tree-based models.
The performance of a random forest can be evaluated using out-of-bag error and cross-validation techniques. Random forests often use random sampling with replacement from the original dataset to create each decision tree. This is also known as bootstrap sampling and forms a bootstrap forest. The data included in the bootstrap sample are referred to as in-the-bag, while the data not selected are out-of-bag. Since the out-of-bag data were not used to generate the decision tree, they can be used as an internal measure of the accuracy of the model. Cross-validation can be used to assess how well the results of a random forest model will generalize to an independent dataset. In this approach, the data are split into a training dataset used to generate the decision trees and build the model and a validation dataset used to evaluate the model’s performance. Evaluating the model on the independent validation dataset provides an estimate of how accurately the model will perform in practice and helps avoid problems such as overfitting or sampling bias. A good model performs well on
both the training data and the validation data.
The complex nature of the EM system made it difficult for the team to identify how various parameters influenced EM behavior. A bootstrap forest analysis was applied to the test dataset and was able to identify five key variables associated with higher probability of damage and/or anomalous behavior. The identified key variables provided a basis for further testing and redesign of the EM system. These results also provided essential insight to the investigation and aided in development of flight rationale for future use cases.
For information, contact Dr. Sara R. Wilson. sara.r.wilson@nasa.gov
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