Space and astronomy news
SpaceX tests all 33 engines on Super Heavy. The worst-case scenario for space debris actually happened. A kilonova is coming. A new map of all the matter and dark matter in the Universe.
Continue reading “AI’s Costly JWST Mistake, 33-Engine Super Heavy Test, Problems in Orbit”
The Hubble Space Telescope recently captured the appearance of several asymmetrical ‘spokes’ rising above the rings of Saturn, marking a coming change in season for the ringed gas giant. The spokes are made of charged ice particles bulging up and away from the rest of the rings. Researchers aren’t sure exactly what causes the spokes, but they suspect it has something to do with the planet’s powerful magnetic fields.
Continue reading “It's Time for Mysterious Spokes to Appear in Saturn's Rings”
Alongside nuclear war or a massive impact from an asteroid, anthropogenic climate change is one of the greatest existential threats facing humanity today. With the rise in greenhouse gas emissions through the 20th century, Earth’s atmosphere continues to absorb more of the Sun’s energy. This has led to rising temperatures, rising sea levels, and increased drought, famine, wildfires, and other ecological consequences. According to the Intergovernmental Panel on Climate Change (IPCC), global temperatures will increase by an average of 1.5 to 2 °C (2.7 to 3.6 °F) by 2050.
For some parts of the world, the temperature increases will be manageable with the right adaptation and mitigation strategies. For others, especially in the equatorial regions (where most of Earth’s population lives), the temperature increases will be severe and will make life untenable for millions of people. For decades, scientists have considered using a sunshield to block a fraction of the Sun’s energy (1 to 2%) before it reaches Earth’s atmosphere. According to a new study by a team led by the University of Utah, lunar dust could be used to shield Earth from sunlight.
Continue reading “Dust From the Moon Could Help the Shade the Earth and Slow Down Climate Change”
Everyone loves taking pictures of the Moon. Whether it’s with their phones or through the wonders of astrophotography, photographing the Moon reminds us about the wonders and awesomeness of the universe. But while we can take awesome images of the whole Moon from the Earth, it’s extremely difficult to get close-up images of its surface given the enormous distance we are from our nearest celestial neighbor at 384,400 km (238,855 mi). This is because the closer we try to zoom in on its surface, the blurrier, or more pixelated, the images become. Essentially, the resolution of the images becomes worse and worse. But what if we could take high-resolution images of the Moon’s surface from Earth instead of relying on satellites presently in lunar orbit to take them for us?
Continue reading “A Green Bank Telescope Prototype Radar System Can Image the Moon in High-Resolution and Detect Asteroids”
The age of big data is upon us, and there are scarcely any fields of scientific research that are not affected. Take astronomy, for example. Thanks to cutting-edge instruments, software, and data-sharing, observatories worldwide are accumulating hundreds of terabytes in a single day and between 100 to 200 Petabytes a year. Once next-generation telescopes become operational, astronomy will likely enter the “exabyte era,” where 1018 bytes (one quintillion) of data are obtained annually. To keep up with this volume, astronomers are turning to machine learning and AI to handle the job of analysis.
While AI plays a growing role in data analysis, there are some instances where citizen astronomers are proving more capable. While examining data collected by the Dark Energy Survey (DES), amateur astronomer Giuseppe Donatiello discovered three faint galaxies that a machine-learning algorithm had apparently missed. These galaxies, all satellites of the Sculptor Galaxy (NGC 253), are now named Donatello II, III, and IV, in his honor. In this day of data-driven research, it’s good to know that sometimes there’s no substitute for human eyeballs and intellect.
Continue reading “Humans Can Still Find Galaxies That Machine Learning Algorithms Miss”
Shackleton Crater at the lunar south pole is one of the locations on NASA’s shortlist for human exploration with the future Artemis missions. But because craters at the lunar poles — like Shackleton — at have areas that are perpetually in shadow, known as permanently shadowed regions (PSRs), we don’t know for sure what lies inside the interior. However, a new spacecraft with a specialized instrument is about to change all that.
Continue reading “New Spacecraft Can See Into the Permanently Shadowed Craters on the Moon”
This week, NASA’s Curiosity rover stumbled across the best evidence yet that liquid water once covered much of Mars in the planet’s distant past: undulating rippled rock formations – now frozen in time – that were sculpted by the waves of an ancient shallow lake. But perhaps the biggest surprise is that they were discovered in an area that researchers expected to be dry.
Continue reading “Curiosity Just Found its Strongest Evidence of Ancient Water and Waves on Mars”
Astronomy has entered the era of big data, where astronomers find themselves inundated with information thanks to cutting-edge instruments and data-sharing techniques. Facilities like the Vera Rubin Observatory (VRO) are collecting about 20 terabytes (TB) of data on a daily basis. Others, like the Thirty-Meter Telescope (TMT), are expected to gather up to 90 TB once operational. As a result, astronomers are dealing with 100 to 200 Petabytes of data every year, and astronomy is expected to reach the “exabyte era” before long.
In response, observatories have been crowdsourcing solutions and making their data open-access so citizen scientists can assist with the time-consuming analysis process. In addition, astronomers have been increasingly turning to machine learning algorithms to help them identify objects of interest (OI) in the Universe. In a recent study, a team led by the University of Georgia revealed how artificial intelligence could distinguish between false positives and exoplanet candidates simultaneously, making the job of exoplanet hunters that much easier.
Continue reading “Machine Learning is a Powerful Tool When Searching for Exoplanets”
You’ve probably never seen our Sun look like this before. This bizarre image of old Sol is made from data produced by three different space telescopes, each observing the Sun at a different wavelength.
Continue reading “Images From Three Telescopes Merged Into One Spectacular Picture of the Sun”
For over sixty years, astronomers and astrophysicists have been engaged in the Search for Extraterrestrial Intelligence (SETI). This consists of listening to other star systems for signs of technological activity (or “technosignatures), such as radio transmissions. This first attempt was in 1960, known as Project Ozma, where famed SETI researcher Dr. Frank Drake (father of the Drake Equation) and his colleagues used the radio telescope at the Green Bank Observatory in West Virginia to conduct a radio survey of Tau Ceti and Epsilon Eridani.
Since then, the vast majority of SETI surveys have similarly looked for narrowband radio signals since they are very good at propagating through interstellar space. However, the biggest challenge has always been how to filter out radio transmissions on Earth – aka. radio frequency interference (RFI). In a recent study, an international team led by the Dunlap Institute for Astronomy and Astrophysics (DIAA) applied a new deep-learning algorithm to data collected by the Green Bank Telescope (GBT), which revealed eight promising signals that will be of interest to SETI initiatives like Breakthrough Listen.
Continue reading “More Data and Machine Learning has Kicked SETI Into High Gear”