CAREER: Physics Implications of the String Landscape via Formal Theory and Data Science

该CAREER奖资助东北大学James Halverson教授的研究和教育/推广活动。弦理论是最小长度尺度物理学理论的主要候选理论。它描述了宇宙的基本组成部分，包括在大型强子对撞机上测量到的相互作用的基本粒子，它还描述了推动宇宙进化的能量来源。这样，弦理论就能够把粒子物理学和宇宙学联系起来。该奖项资助的研究重点是弦理论对这两个学科的影响。有两个主要挑战。首先，弦理论本身的某些方面仍有待了解。特别是，在与数学家的合作中，霍尔沃森将研究弦强相互作用的状态。要全面理解弦的相互作用，有必要改进对这一机制的理解。其次，弦理论预测了大量可能的物理定律——一个被称为弦景观的阵列——这引发了一个问题，即我们观察到的定律是如何在自然界中实现的，以及它们的实现是否会导致对实验的新预测。然而，从实际的角度来看，景观可以被视为一个巨大的数据集。作为该项目的一部分，Halverson将与计算机科学家合作，利用数据科学和机器学习技术来研究景观。该领域的研究通过促进科学在其最基本的方向之一的进步：发现和理解物理定律，从而促进了国家利益。霍尔沃森的研究还将产生更广泛的影响，使新的研究人员群体能够参与进来。这些人包括工业界的专业人士、高中生和互联网数据科学社区。在Halverson的活动中，将为这些社区的成员开发并交付一系列讲座，以便为他们提供在数据科学和弦理论界面进行研究的基本背景信息。从技术上讲，霍尔沃森将对弦理论中的强耦合进行正式研究。他将研究奇异空间上f理论中的弦结，非希格可簇的各方面，以及m理论的G2紧化。他还将使用数据科学技术研究字符串景观中的物理问题，包括监督学习，强化学习和生成对抗网络。将讨论计算复杂性与这些技术在物理问题中的应用之间的相互作用。Halverson还将研究在宇宙中经常出现的低能量自由度的粒子物理学和宇宙学含义，包括那些与大型暗规扇区和弦轴有关的自由度。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This CAREER award funds the research and education/outreach activities of Professor James Halverson at Northeastern University. String theory is the leading candidate for a theory of physics at the smallest length scales. It describes the fundamental building blocks of the universe, including the elementary particles whose interactions are measured at the Large Hadron Collider, and it also describes the sources of energy that drive the evolution of the cosmos. In this way string theory is capable of connecting particle physics and cosmology. The research funded by this award focuses on the implications of string theory for these two disciplines. There are two central challenges. First, certain aspects of string theory proper still remain to be understood. In particular, in collaboration with mathematicians, Halverson will study the regime in which strings interact strongly. An improved understanding of this regime is necessary for a complete understanding of string interactions. Second, string theory predicts a vast array of possible laws of physics --- an array known as the string landscape --- prompting the question of how the laws we observe are realized in nature and whether their realization leads to new predictions for experiments. From a practical point of view, however, the landscape can be viewed as an enormous dataset. As part of this project, Halverson, in collaboration with computer scientists, will therefore utilize techniques from data science and machine learning to study the landscape. Research in this area advances the national interest by promoting the progress of science in one of its most fundamental directions: the discovery and understanding of physical law. Halverson's research will also have significant broader impacts by enabling and engaging new communities of researchers. These include professionals in industry, high-school students, and the internet data-science community. Among Halverson's activities, a lecture series will be developed for and delivered to members of these communities in order to give them the essential background information for carrying out research at the interface of data science and string theory. More technically, Halverson will carry out formal work at strong coupling in string theory. He will study string junctions in F-theory on singular spaces, aspects of non-Higgsable clusters, and G2 compactifications of M-theory. He will also study physical problems in the string landscape using techniques from data science, including supervised learning, reinforcement learning, and generative adversarial networks. The interplay between computational complexity and the use of these techniques in physical problems will be addressed. Halverson will also study the particle physics and cosmological implications of the low-energy degrees of freedom that arise regularly in the landscape, including those associated with large dark gauge sectors and the string axiverse.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.