Conformal invariance and the renormalization group in some critical systems

一些关键系统中的共形不变性和重整化群

• 批准号: 1500850
• 负责人: Thomas Kennedy
• 金额: $ 36.14万
• 依托单位: University of Arizona
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-06-01 至 2020-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1500850&HistoricalAwards=false
• 关键词: Conformal; invariance; renormalization; group; some

Many models in physics are inherently discrete at the very smallest scale (typically the size of an atom) and there is inherent randomness at this discrete level. At the macroscopic level the randomness is typically not seen. But under certain conditions this randomness manifests itself at the macroscopic scale. This is known as a critical phenomena. For example, the spins in a magnetic material have randomness in their orientation. At a certain temperature these spins can align with each other to produce macroscopic magnetic domains that play a crucial role in technological applications such as hard drives. The randomness seen at the macroscopic scale often does not depend on the details of the microscopic randomness. In physics this is called universality and has developed into a key idea in the understanding of critical phenomena. The renormalization group is set of methods from physics that has become the basis for the modern understanding of both critical phenomena and of quantum field theory - the theory of elementary particles. Despite the tremendous success of the renormalization group in physics, we do not have a deep mathematical understanding of this set of ideas. This research will further the mathematical development and understanding of this set of ideas and methods and use them to understand the mathematics of critical phenomena in models such as self-avoiding random walks and Ising models of magnetic spins.Most of the research will be devoted to random walk models and Ising-type models. The smart kinetic walk (also known as a limiting case of the Laplacian-b random walk) is a dynamic model for self-avoiding walks. On the hexagonal lattice it is closely related to percolation. Percolation methods have been used to prove its scaling limit is the Schramm-Loewner evolution with parameter value 6. The research will study this scaling limit on other lattices and for generalizations of the transition probabilities. The goal is to understand the universality of this scaling limit. For the ordinary random walk the scaling limit of the exit distribution for a domain is harmonic measure. Another goal of the research is to understand the first order correction for this convergence for both the ordinary random walk and the smart kinetic walk. The research will also study real space renormalization groups for Ising type models, in particular exact renormalization group transformations in one and two dimensions. These transformation have the potential advantage that the map would act on a finite dimensional space. The goal is to prove that the map can be rigorously defined and then take advantage of the finite dimensional nature to prove existence of a fixed point and all the exciting consequences that follow from this existence. Finally the research will study Schramm-Loewner evolution as a renormalization group fixed point. This stochastic process is known to be the scaling limit of many critical models. The goal here is to define a renormalization group map that has this process as a fixed point and then use this map to understand models that are near criticality.

物理学中的许多模型在最小尺度（通常是原子的大小）上本质上是离散的，并且在这种离散水平上存在固有的随机性。在宏观水平上，通常看不到随机性。但在某些条件下，这种随机性在宏观尺度上表现出来。这被称为临界现象。例如，磁性材料中的自旋在其取向上具有随机性。在一定温度下，这些自旋可以相互对齐，产生宏观磁畴，在硬盘驱动器等技术应用中发挥关键作用。在宏观尺度上看到的随机性往往不依赖于微观随机性的细节。在物理学中，这被称为普遍性，并已发展成为理解临界现象的关键思想。重整化群是物理学中的一套方法，它已经成为现代理解临界现象和量子场论（基本粒子理论）的基础。尽管重正化群在物理学中取得了巨大的成功，但我们对这组思想并没有深刻的数学理解。本研究将进一步数学发展和理解这套思想和方法，并使用它们来理解数学的关键现象的模型，如自避免随机行走和伊辛模型的磁自旋。大部分的研究将致力于随机行走模型和伊辛型模型。智能动态行走（也称为拉普拉斯-b随机行走的极限情况）是一种自我回避行走的动态模型。在六方晶格上，它与渗流密切相关。用逾渗方法证明了它的标度极限是参数值为6的Schramm-Loewner演化。这项研究将研究这种缩放限制在其他晶格和一般化的过渡概率。我们的目标是了解这种缩放限制的普遍性。对于一般的随机游动，区域出口分布的标度极限是调和测度。研究的另一个目标是了解普通随机行走和智能动能行走收敛的一阶校正。研究还将研究伊辛型模型的真实的空间重整化群，特别是一维和二维的精确重整化群变换。这些变换的潜在优点是映射可以作用于有限维空间。目标是证明映射可以被严格定义，然后利用有限维的性质来证明不动点的存在性以及由此产生的所有令人兴奋的后果。最后研究Schramm-Loewner演化作为重整化群不动点的问题。这个随机过程被认为是许多临界模型的尺度极限。这里的目标是定义一个重正化群映射，将这个过程作为一个固定点，然后使用这个映射来理解接近临界的模型。