August 18, 2023: The strongest magnets in the universe, how recommendation algorithms work and the science of nighttime bird calls. —Andrea Gawrylewski, Chief Newsletter Editor | | | A couple days ago, I told you about mysterious and dramatic Wolf-Rayet stars. Now, a new study by astronomers suggests that one Wolf-Rayet, in a star system named HD 45166 some 3,000 light-years from Earth, could transform, in a few million years or so, into an even rarer cosmic body—a magnetar. The Wolf-Rayet star in HD 45166 has a magnetic field of 43,000 gauss (Earth's field, for comparison, is a paltry half-gauss), making it the most magnetic massive star ever discovered. Yet, as titanic as this magnetic field may seem, it pales in comparison to the magnetism that may emerge if this star becomes a magnetar.
Why this is so cool: Magnetars are the most powerful magnets in the known universe, possessing magnetic fields of an estimated 100 trillion gauss. So far, scientists have managed to find only about 30 of them. A supernova can compress massive stars into city-size ultra-dense orbs called neutron stars, of which magnetars are a type. That compression, in part, supercharges any preexisting magnetic field. If a magnetar were placed in the moon's orbit around Earth, it would wipe most credit cards and hard disk drives on the planet; out in the cosmos, these strange objects can unleash intense outbursts visible clear across the universe, making them important beacons for astronomers to study.
What the experts say: "The magnetic field can create so much stress that it'll crack the crust of the star," says Jason Hessels of the University of Amsterdam, "causing a massive star quake that releases a lot of energy." | | | Every day, we encounter algorithms that recommend content or products to us, whether on Spotify, Amazon, Netflix or Instagram. Content providers like these have two primary ways of training their algorithms (on massive amounts of data) to recommend the next show or song to you: One is "collaborative filtering" based on ratings by other users with similar behavior. The second is content-based where users receive recommendations for items similar to what they have positively reviewed previously.
Why this is interesting: To spot patterns in these massive data sets from millions of users, companies use common methods from linear algebra, such as singular value decomposition or principal component analysis (obvs?!). Artificial intelligence models are increasingly used to process these data, and self-learning algorithms are trained to recognize patterns.
What will happen: As AI advances, recommendations will likely improve. BUT, transparency about how the algorithms both obtain their data and crunch it will likely decrease, writes Manon Bischoff, a theoretical physicist and editor at Spektrum, a partner publication of Scientific American. | | | Nighttime Bird Surveillance Network Seventy percent of bird species in North America are migratory, and 80 percent of those migrate at night. The night air is easier to fly through, and the moon and stars aid with navigation. But in the darkness birds can more easily get blown off course or run into obstacles. Birds offset nighttime migratory challenges by calling to each other. The scale of this migration is much larger than scientists once thought, but it is in decline now as bird populations plummet. Our new five-part podcast mini-series, hosted by ecologist and nature lover Jacob Job, will investigate the science of nocturnal flight calls and how this research is being used to protect migratory birds.
| | | • Extreme temperatures across the U.S. this year could kill twice as many people as usual. | 9 min read | | | • The mathematical "hairy ball theorem" is a discovery from a branch of math called topology, and has implications for global weather patterns, radio transmissions and nuclear power (straight faces, everyone). | 7 min read | | | • Between 50,000 and 10,000 years ago, naturally occurring asphalt in the Los Angeles La Brea "tar pits" trapped hundreds of organisms. The fossils of those creatures are helping scientists reconstruct the ecology of that time. | 4 min read | | | A composite saber-toothed tiger skeleton found at the La Brea tar pits in California. Credit: PF-(bygone1)/Alamy Stock Photo | | | • The story of J. Robert Oppenheimer and his peers shows that scientists have a duty to engage with politics and that failing to speak out carries its own consequences, writes Dan Correa, CEO of the Federation of American Scientists. We should "take inspiration from its story of scientists courageously engaging directly in politics. Especially when it wasn't popular," he says. | 3 min read | | | ICYMI (Our most-read stories of the week) | | | • Neuroscientists Re-create Pink Floyd Song from Listeners' Brain Activity | 5 min read | | | • The Superconductor Sensation Has Fizzled, and That's Fine | 6 min read | | | • Why a Banyan Tree Damaged in the Maui Wildfire Was So Beloved | 5 min read | | | I've been eagerly awaiting our newest podcast mini-series by Jacob Job, which I hope you tune into. And when you're done, check out Job's other podcast series for Scientific American, "National Park Nature Walks," from 2021. It's one of my favorite podcasts, and hearing the sounds of a thunderstorm over the Rocky Mountains or the wind at 250 feet above Sequoia National Park is the perfect way to unwind from a long week. | I hope you've enjoyed Today in Science this week. Reach out anytime with suggestions: newsletters@sciam.com. See you on Monday! | —Andrea Gawrylewski, Chief Newsletter Editor | | Subscribe to this and all of our newsletters . | | | | Scientific American
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