The goal of identifying the Standard Model of particle physics and its extensions within string theory has been one of the principal driving forces in string phenomenology. Recently, the incorporation of artificial intelligence in string theory and certain theoretical advancements have brought to light unexpected solutions to mathematical hurdles that have so far hindered progress in this direction. In this review we focus on model building efforts in the context of the $E_8\times E_8$ heterotic string compactified on smooth Calabi-Yau threefolds and discuss several areas in which machine learning is expected to make a difference.
翻译：确定粒子物理学标准模型及其在弦理论中的延伸,一直是弦毒理学的主要驱动力之一。最近,将人工智能纳入弦理论和某些理论进步,揭示出迄今为止阻碍这方面进展的数学障碍的出人意料的解决办法。在本次审查中,我们侧重于在“$E_8time E_8$ exterography string ” 背景下的模型建设努力,该模型压缩在平滑的Calabi-Yau三重线上,并讨论了机器学习预期能发挥作用的几个领域。
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