Reconsidering the Approach to Mountain Height Measurement?
In a groundbreaking development, Kai Xu, a doctoral student in computer science at New York University, has devised a new metric for measuring mountains – one that takes into account both a mountain's height above its surroundings and the steepness of its rise. This innovative approach, which Xu calls "jut," is shaking up the world of mountaineering and geography.
Xu's interest in mountains was sparked at the tender age of 19, when he found himself gazing upon Mount Tom, a 13,652-foot peak in California's Eastern Sierra Nevada range. This encounter ignited a lifelong passion for the majestic peaks that have since influenced his academic pursuits.
While studying at Yale University as a double major in applied mathematics and computer science, Xu set out to devise an equation that would rearrange the hierarchy of the planet's mightiest mountains and introduce a new tool for seeking them out. His hard work paid off, and the results were published on arXiv.org.
Xu's new metric, jut, has already caused a stir among mountaineers, hikers, and geographers, reigniting debates over what truly makes a mountain great. In Xu's ranking, Mount Everest, the world's ostensibly loftiest peak, drops to 46th place. Instead, Annapurna Fang, a 25,089-foot Himalayan peak with an impressive 11,1194 feet of jut, takes the top spot as the most impressive summit.
Xu's website, peakjut.com, allows users to surf customizable lists of mountains ranked by jut, search by location for high-jut peaks, and find coordinates for a mountain's most impressive viewpoint. Users can also explore a worldwide "heat map" of jut, created by software developer and backpacker Noah Lomas, who added this feature to Xu's site earlier this year.
With peakjut.com, Xu aims to steer users to some of the best mountain views in their own backyard, even helping them take that perfect Instagram photo. The website's user-friendly interface and customizable features make it an invaluable resource for both seasoned mountaineers and casual hikers alike.
Despite living just a few hours away from the Eastern Sierra escarpment, Xu had never visited the area until recently. His work on jut has undoubtedly expanded his own horizons, and he continues to explore new ways in which artificial intelligence can reveal remote subranges and unnamed summits.
Xu's posts on Reddit explaining his new system have garnered thousands of comments, demonstrating the widespread interest in his innovative approach to mountain measurement. As the mountaineering community continues to debate the merits of jut, one thing is clear: Kai Xu's work is transforming the way we think about and explore the world's most majestic peaks.
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