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

该职业奖资助东北大学教授James Halverson的研究和教育/推广活动。弦理论是最小尺度物理学理论的主要候选者。 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其相互作用的基本粒子，它还描述了驱动宇宙演化的能量来源。 这样一来，弦理论就能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理解。特别是，在与数学家合作，Halverson将研究的制度，其中字符串强烈相互作用。要想完全理解弦的相互作用，就必须更好地理解这种状态。第二，弦理论预言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如何在自然界中实现，以及它们的实现是否会导致新的实验预测。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。 这一领域的研究通过促进科学在其最基本的方向之一的进步来促进国家利益： 物理定律的发现和理解。 Halverson的研究还将通过启用和吸引新的研究人员社区来产生更广泛的影响。其中包括行业专业人士，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提供一系列讲座，以便为他们提供在数据科学和弦理论的接口进行研究的基本背景信息。从技术上讲，Halverson将在弦理论中的强耦合方面进行正式的工作。他将研究弦结F-理论奇异空间，方面的非Higgsable集群，和G2紧化的M-理论。他还将使用数据科学技术研究弦景观中的物理问题，包括监督学习，强化学习和生成对抗网络。计算的复杂性和使用这些技术在物理问题之间的相互作用将得到解决。Halverson还将研究粒子物理学和宇宙学意义的低能量自由度，经常出现在景观，包括那些与大型暗规范部门和弦轴向。这个奖项反映了NSF的法定使命，并已被认为是值得通过评估使用基金会的智力价值和更广泛的影响审查标准的支持。

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.