The Verge: This nonprofit plans to send millions of Wikipedia pages to the Moon — printed on tiny metal sheets. “A nonprofit with grand ambitions of setting up a library on the Moon is planning to send the entire English archive of Wikipedia to the lunar surface sometime within the next couple of years. Don’t worry: there won’t be reams of Wikipedia printouts sitting in the lunar soil. Instead, the organization says it will send up millions of Wikipedia articles in the form of miniaturized prints, etched into tiny sheets of metal that are thinner than the average human hair. The nonprofit claims that with this method, it can send up millions of pages of text in a package that’s about the size of a CD.”
Science Alert: You Can Now Listen to The Weird ‘Music’ Made by Our Rotating Galaxy. “Ever wondered what the Milky Way might sound like as it rotates on its axis? According to a new ‘musical expression’ by an astronomer, it has distinctly jazz-like tones. Mark Heyer of the University of Massachusetts Amherst developed an algorithm that expresses the movement of gases in the Milky Way’s disc as musical notes. He’s titled the resulting composition Milky Way Blues.” The end of the article features a pointer to a new Web site called “Astronomy Sound of the Month”.
New Scientist: Biggest ever 3D map of the galaxy pinpoints 1.7 billion stars. “We’re building a map of our galaxy, one star at a time. The European Space Agency’s Gaia satellite orbits Earth 1.5 million kilometres away, staring at millions of stars every day to make a 3D map of our galaxy. On 25 April it released its second batch of data. In 2016, Gaia first released data from its star catalog spanning 14 months of constant observation. It included information about the brightness and positions in the sky of 1.1 billion stars, and more detailed data on the distances and motions of the brightest two million of those. This new data release is even more robust, covering another 22 months of observation time. It includes more stars than the first release, and the colours, temperatures, and radii for some of those stars.”
ScienceBlog: Computer Searches Telescope Data For Evidence Of Distant Planets. “As part of an effort to identify distant planets hospitable to life, NASA has established a crowdsourcing project in which volunteers search telescopic images for evidence of debris disks around stars, which are good indicators of exoplanets. Using the results of that project, researchers at MIT have now trained a machine-learning system to search for debris disks itself. The scale of the search demands automation: There are nearly 750 million possible light sources in the data accumulated through NASA’s Wide-Field Infrared Survey Explorer (WISE) mission alone.”
Google Open Source Blog: Open Sourcing the Hunt for Exoplanets. “Recently, we discovered two exoplanets by training a neural network to analyze data from NASA’s Kepler space telescope and accurately identify the most promising planet signals. And while this was only an initial analysis of ~700 stars, we consider this a successful proof-of-concept for using machine learning to discover exoplanets, and more generally another example of using machine learning to make meaningful gains in a variety of scientific disciplines (e.g. healthcare, quantum chemistry, and fusion research). Today, we’re excited to release our code for processing the Kepler data, training our neural network model, and making predictions about new candidate signals.”
Engadget: Google’s $20 million Lunar Xprize will end without a winner. “The Lunar Xprize is about to come to an anticlimactic end after more than a decade. Google has confirmed to CNBC that it doesn’t plan to extend the $20 million competition past its March 31st deadline — itself an extension well beyond the original 2014 end date. Given that all the finalists either don’t have the funds to continue or don’t expect to launch that quickly (the fastest, SpaceIL, might not launch before the end of 2018), the competition is effectively over with no winners. Not that Google minds, however.”
Phys.org: Dark Energy Survey publicly releases first three years of data. “At a special session held during the American Astronomical Society meeting in Washington, D.C., scientists on the Dark Energy Survey (DES) announced today the public release of their first three years of data. This first major release of data from the Survey includes information on about 400 million astronomical objects, including distant galaxies billions of light-years away as well as stars in our own galaxy.”