Rhea, an icy cratered moon that provided the first direct evidence of an oxygen atmosphere in the Saturn system, shines in its final image by the Cassini spacecraft.
The Cassini spacecraft explored Saturn and its many moons for 13 years before plunging into the ringed planet on Sept. 15 of this year. It was a cooperative mission conducted by NASA, the European Space Agency (ESA) and the Italian Space Agency. The narrow-angle camera on the probe captured this bird's-eye view of Rhea's northern hemisphere on May 2, 2017. Cassini was "high above the plane of Saturn's rings" when it made its final observation of Rhea at a distance of about 230,000 miles (370,000 kilometers) from the moon. Rhea has a reflective surface because the moon is mostly made of ice, maintained by frigid temperatures: Sunlit areas are about minus 174 degrees Celsius (minus 281 degrees Fahrenheit), and regions in the dark can reach minus 220 degrees C (minus degrees 364 F), NASA officials said in the statement. Rhea is the second largest moon in orbit around Saturn, at about 949 miles (1,527 kilometers) across, and was one of the four moons spotted in 1672 by astronomer Giovanni Cassini. Initially named "Saturn V," the moon was later renamed in 1847 to Rhea, the goddess wife of Cronos in Greek mythology. Cronos, in Roman mythology, was known as Saturn. Rhea has an oxygen atmosphere that is about 5 trillion times less dense than Earth's atmosphere. Some scientists propose that the oxygen atmosphere is caused by the icy surface getting exposure to radiation from Saturn's magnetosphere, according to the statement.
0 Comments
Our solar system now is tied for most number of planets around a single star, with the recent discovery of an eighth planet circling Kepler-90, a Sun-like star 2,545 light-years from Earth. The planet was discovered in data from NASA’s Kepler Space Telescope. The newly-discovered Kepler-90i – a sizzling hot, rocky planet that orbits its star once every 14.4 days – was found using machine learning from Google. Machine learning is an approach to artificial intelligence in which computers “learn.” In this case, computers learned to identify planets by finding in Kepler data instances where the telescope recorded signals from planets beyond our solar system, known as exoplanets. Credits:NASA “Just as we expected, there are exciting discoveries lurking in our archived Kepler data, waiting for the right tool or technology to unearth them,” said Paul Hertz, director of NASA’s Astrophysics Division in Washington. “This finding shows that our data will be a treasure trove available to innovative researchers for years to come.”
The discovery came about after researchers Christopher Shallue and Andrew Vanderburg trained a computer to learn how to identify exoplanets in the light readings recorded by Kepler – the minuscule change in brightness captured when a planet passed in front of, or transited, a star. Inspired by the way neurons connect in the human brain, this artificial “neural network” sifted through Kepler data and found weak transit signals from a previously-missed eighth planet orbiting Kepler-90, in the constellation Draco. While machine learning has previously been used in searches of the Kepler database, this research demonstrates that neural networks are a promising tool in finding some of the weakest signals of distant worlds. Other planetary systems probably hold more promise for life than Kepler-90. About 30 percent larger than Earth, Kepler-90i is so close to its star that its average surface temperature is believed to exceed 800 degrees Fahrenheit, on par with Mercury. Its outermost planet, Kepler-90h, orbits at a similar distance to its star as Earth does to the Sun. “The Kepler-90 star system is like a mini version of our solar system. You have small planets inside and big planets outside, but everything is scrunched in much closer,” said Vanderburg, a NASA Sagan Postdoctoral Fellow and astronomer at the University of Texas at Austin. Shallue, a senior software engineer with Google’s research team Google AI, came up with the idea to apply a neural network to Kepler data. He became interested in exoplanet discovery after learning that astronomy, like other branches of science, is rapidly being inundated with data as the technology for data collection from space advances. “In my spare time, I started googling for ‘finding exoplanets with large data sets’ and found out about the Kepler mission and the huge data set available,” said Shallue. "Machine learning really shines in situations where there is so much data that humans can't search it for themselves.” Kepler’s four-year dataset consists of 35,000 possible planetary signals. Automated tests, and sometimes human eyes, are used to verify the most promising signals in the data. However, the weakest signals often are missed using these methods. Shallue and Vanderburg thought there could be more interesting exoplanet discoveries faintly lurking in the data. First, they trained the neural network to identify transiting exoplanets using a set of 15,000 previously-vetted signals from the Kepler exoplanet catalogue. In the test set, the neural network correctly identified true planets and false positives 96 percent of the time. Then, with the neural network having "learned" to detect the pattern of a transiting exoplanet, the researchers directed their model to search for weaker signals in 670 star systems that already had multiple known planets. Their assumption was that multiple-planet systems would be the best places to look for more exoplanets. “We got lots of false positives of planets, but also potentially more real planets,” said Vanderburg. “It’s like sifting through rocks to find jewels. If you have a finer sieve then you will catch more rocks but you might catch more jewels, as well.” Kepler-90i wasn’t the only jewel this neural network sifted out. In the Kepler-80 system, they found a sixth planet. This one, the Earth-sized Kepler-80g, and four of its neighboring planets form what is called a resonant chain – where planets are locked by their mutual gravity in a rhythmic orbital dance. The result is an extremely stable system, similar to the seven planets in the TRAPPIST-1 system. Kepler has produced an unprecedented data set for exoplanet hunting. After gazing at one patch of space for four years, the spacecraft now is operating on an extended mission and switches its field of view every 80 days. “These results demonstrate the enduring value of Kepler’s mission,” said Jessie Dotson, Kepler’s project scientist at NASA’s Ames Research Center in California’s Silicon Valley. “New ways of looking at the data – such as this early-stage research to apply machine learning algorithms – promises to continue to yield significant advances in our understanding of planetary systems around other stars. I’m sure there are more firsts in the data waiting for people to find them.” NASA A supermoon happens when the full moon coincides with the moon's closest approach to Earth in its orbit. Supermoons make the moon appear a little brighter and closer than normal, although the difference is hard to spot with the naked eye. The last supermoon (the only one of 2017) happened on Dec. 3. It kicked off a trilogy of consecutive supermoons; the next ones happen on Jan. 1 and Jan. 31. The Jan. 31 supermoon will also coincide with a lunar eclipse best visible in the western United States, the Pacific and eastern Asia. The term "supermoon" has only been used in the past 40 years, but it received a slew of attention in late 2016 when three supermoons occurred in a row. The supermoon of November 2016 was also the closest supermoon in 69 years, although a closer supermoon will rise in the 2030s. How a supermoon happens The moon's orbit around the Earth is not a perfect circle. It has an average distance of 238,000 miles (382,900 km) from Earth, but its apogee and perigee — the closest and farthest approaches from Earth — change every lunar month. "The main reason why the orbit of the moon is not a perfect circle is that there are a lot of tidal, or gravitational, forces that are pulling on the moon," said NASA's Noah Petro, deputy scientist of the Lunar Reconnaissance Orbiter mission. He added that the different gravities of the Earth, sun and planets all have an effect on the moon's orbit. "You have all of these different gravitational forces pulling and pushing on the moon, which gives us opportunities to have these close passes." A supermoon needs two key ingredients to occur. The moon needs to be at its closest approach, or perigee, to the Earth in its 27-day orbit. The moon also needs to be at the full phase, which happens every 29.5 days when the sun fully illuminates the moon. Supermoons only happen a few times a year (at most) because the moon's orbit changes orientation while the Earth orbits the sun — that's why you don't see a supermoon every month. The moon will appear as much as 30 percent brighter and 14 percent larger than usual, but it's very hard to spot the difference with the naked eye. That's not enough to notice unless you're a very careful moon-watcher. The supermoon may look especially large to you, however, if it's very close to the horizon. But that has nothing to do with astronomy and everything to do with how the human brain works. This effect is called the "moon illusion" and may arise from at least a couple of different things. Scientists suggest that perhaps the brain is comparing the moon to nearby buildings or objects, or perhaps our brain is just wired to process things on the horizon as bigger than things in the sky. |
ArchivesCategories |