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

该职业奖资助东北大学詹姆斯·哈尔弗森教授的研究和教育/外展活动。弦理论是最小尺度的物理理论的主要候选者。它描述了宇宙的基本组成部分，包括基本粒子，它们的相互作用是在大型强子对撞机上测量的，它还描述了推动宇宙演化的能量来源。通过这种方式，弦理论能够将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。这里有两个核心挑战。首先，弦理论本身的某些方面仍有待理解。特别是，在与数学家的合作中，哈尔弗森将研究弦之间强烈相互作用的机制。为了完全理解弦相互作用，有必要更好地理解这一机制。第二，弦理论预测了大量可能的物理定律-一组被称为弦景观的数组-引发了我们观察到的定律在自然界中是如何实现的问题，以及它们的实现是否会导致对实验的新预测。然而，从实践的角度来看，这一景观可以被视为一个巨大的数据集。因此，作为该项目的一部分，哈尔弗森将与计算机科学家合作，利用数据科学和机器学习的技术来研究地形。这一领域的研究通过促进科学在其最基本的方向之一--发现和理解物理定律--的进步来促进国家利益。哈尔弗森的研究还将通过支持和参与新的研究人员社区而产生重大的更广泛的影响。这些人包括工业界的专业人士、高中生和互联网数据科学界。在哈尔弗森的活动中，将为这些社区的成员开发并向他们提供系列讲座，以便为他们提供在数据科学和弦理论的界面上开展研究的基本背景信息。更严格地说，哈尔弗森将在弦理论中进行强耦合的形式工作。他将研究奇异空间上F-理论中的弦连接，非Higgsable簇的方面，以及M-理论的G2紧化。他还将使用数据科学中的技术来研究弦环境中的物理问题，包括监督学习、强化学习和生成性对抗网络。计算复杂性和这些技术在物理问题中的使用之间的相互作用将被解决。哈尔弗森还将研究景观中经常出现的低能量自由度的粒子物理和宇宙学影响，包括与大暗规扇区和弦轴相关的自由度。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势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.