论文标题
弦理论景观的智能探索
Intelligent Explorations of the String Theory Landscape
论文作者
论文摘要
识别粒子物理的标准模型及其在字符串理论中的扩展的目的一直是弦现象学中的主要驱动力之一。最近，人工智能在弦理论中的结合和某些理论进步已引发了对数学障碍的意外解决方案，而数学障碍已经阻碍了这一方向的进步。在这篇综述中，我们将重点放在模型建立努力的背景下，以$ e_8 \ times e_8 $杂丝串在平滑的calabi-yau三倍上压实，并讨论了预计机器学习会有所作为的几个领域。
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.
