Galactic Waves, Clean Energy From AI, and Seeing Around Corners

Galactic Waves, Clean Energy From AI, and Seeing Around Corners

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There’s a Wave in Our Galaxy…and It Might Have Passed Through Us

A diagram illustrating the Radcliffe Wave. The white line represents its current position, with blue blobs representing star clusters. The green and purple lines indicate future positions. The yellow dot is the Sun. Image: Ralf Konietzka et al, Nature (2024).

A few years ago, scientists discovered a gigantic 9,000 light-year-long gaseous wave in the spiral arms of our Milky Way galaxy. Scientists are still unraveling details about the structure, which has been dubbed the Radcliffe Wave, and a team at Harvard University has just learned the wave is actually “waving”. The team used measurements taken by ESA’s Gaia Spacecraft to track star position and velocity of baby stars born along the wave. These measurements revealed the Radcliffe wave is oscillating as a periodic traveling wave, which seems to be driven by the gravitational pull of the Milky Way itself. Since it’s virtually next door to our solar system, our own sun likely passed through the wave about 13 million years ago.Press release here, paper here.

This episode of Science News covers several recent discoveries of naturally occurring hydrogen reservoirs underground (the so-called "white hydrogen") that have prompted the whole world to start searching for more of the stuff. Even though this seems like a gamechanger for the hydrogen economy, I am still skeptical of its viability economically, energetically, and environmentally. You can take the quiz here.

AI-Driven Fusion Control Promises Cleaner Energy Future

Nuclear energy plus AI may sound scary, but here is an example where AI is contributing to nuclear efficiency and safety. Experiments at the DIII-D National Fusion Facility in San Diego confirm that a Princeton team of engineers, physicists, and data scientists have successfully trained an AI neural network to predict and prevent instabilities in Tokamak fusion reactors. The AI neural network was able to predict instabilities in the magnetic fields of plasmas in Tokamak reactors about 300 milliseconds in advance, long enough to adjust operating parameters to prevent the instabilities. This achievement comes after similar work by Deepmind and researchers in China who used AI to control nuclear plasma, but not with a focus on instabilities. Watch one of my YouTube videos about similar work here, check out the press release here, or read the full paper here.

Separate Truth from Fiction with Scientific Precision

Ground News, developed by former NASA engineer Harleen Kaur, is a comprehensive news website and app. Its platform aggregates related articles from more than 50,000 sources worldwide, allowing easy comparison on any topic. With context on each source's political bias, reliability, and ownership, readers are empowered to distinguish fact from fiction. And with its transparent and data-driven rating system, Ground News promotes exploration of diverse viewpoints conveniently in one place. Rest assured you accurately understand current events with access to primary sources alongside how the news interprets it.

Scientists Figure Out How to See Around Corners

Scientists from the University of South Florida have done the seemingly impossible: see around corners. They developed a computer algorithm that can use subtle information in faint shadows and reflections to reconstruct a 3-dimensional image of objects behind obstacles. The applications are far-reaching, potentially not only preventing automobile accidents but also aiding law enforcement during hostage situations, facilitating search-and-rescue missions, and enhancing military strategies.Unlike previous attempts that required specialized, expensive equipment, this research achieves 3D imaging results using standard digital cameras. The researchers stress it is low-cost, does not require much equipment, and provides an accessible avenue for future applications. While the devices are currently in the development phase and not yet robust enough for rapid adoption, the algorithm is available open source for testing by other researchers. Watch a video about the development here, read a press release here, and the full paper here. If you are a savvy programmer check out the full algorithm here on GitHub.

Our podcast “Science with Sabine” is available on Spotify, Amazon, Apple, Castbox, Google Podcasts, Pocket CastsRadio Public, and YouTube.

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