{"id":15346,"date":"2017-12-15T15:00:39","date_gmt":"2017-12-15T20:00:39","guid":{"rendered":"http:\/\/hobbyspace.com\/Blog\/?p=15346"},"modified":"2017-12-15T12:07:08","modified_gmt":"2017-12-15T17:07:08","slug":"video-google-neural-network-used-to-discover-exoplanet","status":"publish","type":"post","link":"https:\/\/hobbyspace.com\/Blog\/?p=15346","title":{"rendered":"Video: Google neural network used to discover exoplanet"},"content":{"rendered":"<p>A NASA \/ Google collaboration used artificial intelligence (AI) techniques to discover an eighth planet around the star\u00a0Kepler-90i, which resides just over 2500 light years from earth.<\/p>\n<ul>\n<li><a href=\"https:\/\/exoplanets.nasa.gov\/news\/1476\/discovery-of-eight-planets-makes-alien-system-the-first-to-tie-with-our-solar-system\/\">Discovery of eight planets makes alien system the first to tie with our solar system &#8211; NASA<\/a><\/li>\n<li><a href=\"https:\/\/www.theverge.com\/2017\/12\/14\/16777394\/google-nasa-ai-machine-learning-planets-astronomy\">Google&#8217;s AI found an overlooked exoplanet &#8211; The Verge<\/a><\/li>\n<\/ul>\n<p>Here is the NASA press release:<\/p>\n<p style=\"text-align: center;\"><strong><a href=\"https:\/\/www.nasa.gov\/press-release\/artificial-intelligence-nasa-data-used-to-discover-eighth-planet-circling-distant-star\" target=\"_d\">Artificial Intelligence, NASA Data Used to Discover Exoplanet | NASA<\/a><\/strong><\/p>\n<p><span class=\"embed-youtube\" style=\"text-align:center; display: block;\"><iframe loading=\"lazy\" class=\"youtube-player\" width=\"1600\" height=\"900\" src=\"https:\/\/www.youtube.com\/embed\/0uzv-tEa7SI?version=3&#038;rel=1&#038;showsearch=0&#038;showinfo=1&#038;iv_load_policy=1&#038;fs=1&#038;hl=en&#038;autohide=2&#038;wmode=transparent\" allowfullscreen=\"true\" style=\"border:0;\" sandbox=\"allow-scripts allow-same-origin allow-popups allow-presentation allow-popups-to-escape-sandbox\"><\/iframe><\/span><\/p>\n<p>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\u2019s Kepler Space Telescope.<\/p>\n<p>The newly-discovered Kepler-90i \u2013 a sizzling hot, rocky planet that orbits its star once every 14.4 days \u2013 was found using machine learning from Google. Machine learning is an approach to artificial intelligence in which computers \u201clearn.\u201d 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.<\/p>\n<p>NASA will host a\u00a0<a href=\"https:\/\/www.reddit.com\/r\/science\/comments\/7jrexn\/science_ama_series_were_planet_hunters_from_nasa\/\">Reddit Ask Me Anything<\/a>\u00a0at 3 p.m. EST [Thursday, Dec.14.2017] on this discovery.<\/p>\n<p style=\"padding-left: 30px;\"><em>\u201cJust as we expected, there are exciting discoveries lurking in our archived Kepler data, waiting for the right tool or technology to unearth them,\u201d said Paul Hertz, director of NASA\u2019s Astrophysics Division in Washington. \u201cThis finding shows that our data will be a treasure trove available to innovative researchers for years to come.\u201d\u00a0<\/em><\/p>\n<p>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 \u2013 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 \u201cneural network\u201d sifted through Kepler data and found weak transit signals from a previously-missed eighth planet orbiting Kepler-90, in the constellation Draco.<\/p>\n<p>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.<\/p>\n<p>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.<\/p>\n<p style=\"padding-left: 30px;\"><em>\u201cThe 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,\u201d said Vanderburg,\u00a0a NASA Sagan Postdoctoral Fellow and astronomer at the University of Texas at Austin.<\/em><\/p>\n<p>Shallue, a senior software engineer with Google\u2019s 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.<\/p>\n<p style=\"padding-left: 30px;\"><em>\u201cIn my spare time, I started googling for \u2018finding exoplanets with large data sets\u2019 and found out about the Kepler mission and the huge data set available,\u201d said Shallue. &#8220;Machine learning really shines in situations where there is so much data that humans can&#8217;t search it for themselves.\u201d<\/em><\/p>\n<p>Kepler\u2019s 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.<\/p>\n<p>First, they trained the neural network to identify transiting exoplanets using a set of\u00a015,000 previously-vetted signals from the Kepler exoplanet catalogue. In the test set,\u00a0the neural network correctly identified true planets and false positives 96 percent of the time. Then, with the neural network having &#8220;learned&#8221; 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.<\/p>\n<p style=\"padding-left: 30px;\"><em>\u201cWe got lots of false positives of planets, but also potentially more real planets,\u201d said Vanderburg. \u201cIt\u2019s 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.\u201d<\/em><\/p>\n<p>Kepler-90i wasn\u2019t 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 \u2013 where planets are locked by their mutual gravity in a rhythmic orbital dance.\u00a0The result is an extremely stable system, similar to the seven planets in the\u00a0<a href=\"https:\/\/exoplanets.nasa.gov\/news\/1419\/nasa-telescope-reveals-largest-batch-of-earth-size-habitable-zone-planets-around-single-star\/\" target=\"_blank\" rel=\"noopener\">TRAPPIST-1 system<\/a>.<\/p>\n<p>Their\u00a0<a href=\"https:\/\/www.cfa.harvard.edu\/~avanderb\/kepler90i.pdf\" target=\"_blank\" rel=\"noopener\">research paper<\/a>\u00a0reporting these findings has been accepted for publication in The Astronomical Journal. Shallue and Vanderburg plan to apply their neural network to Kepler\u2019s full set of more than 150,000 stars.<\/p>\n<p>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.<\/p>\n<p style=\"padding-left: 30px;\"><em>\u201cThese results demonstrate the enduring value of Kepler\u2019s mission,\u201d said Jessie Dotson, Kepler\u2019s project scientist at NASA\u2019s Ames Research Center in California\u2019s Silicon Valley. \u201cNew ways of looking at the data \u2013 such as this early-stage research to apply machine learning algorithms \u2013 promises to continue to yield significant advances in our understanding of planetary systems around other stars. I\u2019m sure there are more firsts in the data waiting for people to find them.\u201d<\/em><\/p>\n<p>Ames manages the Kepler and K2 missions for NASA\u2019s Science Mission Directorate in Washington. NASA&#8217;s Jet Propulsion Laboratory in Pasadena, California, managed Kepler mission development. Ball Aerospace &amp; Technologies Corporation operates the flight system with support from the Laboratory for Atmospheric and Space Physics at the University of Colorado in Boulder. This work was performed through the Carl Sagan Postdoctoral Fellowship Program executed by the NASA Exoplanet Science Institute.<\/p>\n<p>For more information on this announcement, visit:\u00a0<a href=\"https:\/\/www.nasa.gov\/mediaresources\" target=\"_blank\" rel=\"noopener\">https:\/\/www.nasa.gov\/mediaresources<\/a><\/p>\n<p>For more information about the Kepler mission, visit:\u00a0<a href=\"https:\/\/www.nasa.gov\/kepler\" target=\"_blank\" rel=\"noopener\">https:\/\/www.nasa.gov\/kepler<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>A NASA \/ Google collaboration used artificial intelligence (AI) techniques to discover an eighth planet around the star\u00a0Kepler-90i, which resides just over 2500 light years from earth. Discovery of eight planets makes alien system the first to tie with our solar system &#8211; NASA Google&#8217;s AI found an overlooked exoplanet &#8211; The Verge Here is &hellip; <a href=\"https:\/\/hobbyspace.com\/Blog\/?p=15346\" class=\"more-link\">Continue reading <span class=\"screen-reader-text\">Video: Google neural network used to discover exoplanet<\/span> <span class=\"meta-nav\">&rarr;<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[12,46],"tags":[],"class_list":["post-15346","post","type-post","status-publish","format-standard","hentry","category-astronomy","category-exoplanets"],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"jetpack_shortlink":"https:\/\/wp.me\/p34aWK-3Zw","jetpack-related-posts":[{"id":15792,"url":"https:\/\/hobbyspace.com\/Blog\/?p=15792","url_meta":{"origin":15346,"position":0},"title":"Videos: TESS to search nearby stars for exoplanets + Using AI to find exoplanets","author":"TopSpacer","date":"March 31, 2018","format":false,"excerpt":"The\u00a0space telescope\u00a0TESS (Transiting Exoplanet Survey Satellite)\u00a0is set to be launched on April 16th on a SpaceX Falcon 9 rocket. 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