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AI Starts to Sift Through String Theory’s Near-Endless Possibilities

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Manage episode 446815329 series 3610709
内容由Alan Jones提供。所有播客内容(包括剧集、图形和播客描述)均由 Alan Jones 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品,您可以按照此处概述的流程进行操作https://zh.player.fm/legal

In this episode of Science Cliff Notes, we discuss an article from Quanta Magazine by Charlie Wood, AI Starts to sift Through String Theory's Near-Endless Possibilities. We will delve into string theory, a potential theory of everything suggesting that the universe is made up of vibrating strings in 10 dimensions. Based on a recent article, we discuss how physicists are employing machine learning algorithms to explore these strings and their configurations, particularly the six small dimensions coiled into shapes known as Calabi-Yau manifolds. Researchers are modeling these manifolds to understand their role in the formation of elementary particles. Recent breakthroughs have seen scientists utilize neural networks to calculate particle masses from specific Calabi-Yau manifolds, marking significant progress towards determining whether these theoretical shapes can explain the properties of our real universe.
https://www.quantamagazine.org/ai-starts-to-sift-through-string-theorys-near-endless-possibilities-20240423/

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Manage episode 446815329 series 3610709
内容由Alan Jones提供。所有播客内容(包括剧集、图形和播客描述)均由 Alan Jones 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品,您可以按照此处概述的流程进行操作https://zh.player.fm/legal

In this episode of Science Cliff Notes, we discuss an article from Quanta Magazine by Charlie Wood, AI Starts to sift Through String Theory's Near-Endless Possibilities. We will delve into string theory, a potential theory of everything suggesting that the universe is made up of vibrating strings in 10 dimensions. Based on a recent article, we discuss how physicists are employing machine learning algorithms to explore these strings and their configurations, particularly the six small dimensions coiled into shapes known as Calabi-Yau manifolds. Researchers are modeling these manifolds to understand their role in the formation of elementary particles. Recent breakthroughs have seen scientists utilize neural networks to calculate particle masses from specific Calabi-Yau manifolds, marking significant progress towards determining whether these theoretical shapes can explain the properties of our real universe.
https://www.quantamagazine.org/ai-starts-to-sift-through-string-theorys-near-endless-possibilities-20240423/

  continue reading

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