Phase Transitions and Scaling Limits in Lattice Models

相变，从熟悉的现象，如液态水冻结成冰的技术关键现象，如过渡到超导性，在自然界中无处不在，一直是数学和物理研究的一个活跃话题，只要科学存在，并继续构成重要的研究挑战。格子模型是为研究自然相变而构造的，是依赖于连续参数的图子集上的概率分布。本研究计划将研究几种重要的晶格模型的相变，包括（1）约束渗流模型，它随机分配“0”或“1”到图的每个顶点，满足代表分子结构方面的约束;和（2）自避免行走，这是一条在图上访问每个顶点最多一次的路径，作为长链聚合物的模型引入。这项工作将拓宽和深化该学科的数学基础，在理论物理和化学中具有潜在的重要应用。研究者的目标是发展有关某些晶格模型相变的新理论。在渗流模型中施加约束通常会使模型失去随机单调性，而在无约束的情况下，这对于研究无限团簇行为所描述的相变是至关重要的。该项目的一个目标是开发新的组合和概率技术，以研究无限集群的行为，而不使用随机单调性。由于非马尔可夫结构，枚举自避免行走通常很困难。连接常数和自避免行走指数是底层图的基本性质，但可以确定为极少数图。这个项目的另一个目标是获得关于大类图的连接常数和指数的新信息，这可以通过分析图上的调和函数来实现。在二维中，中心极限定理的一个类似物是某些晶格模型的高度函数在临界状态（即相变发生时）的极限形状行为。研究人员还计划使用复分析和代数几何的技术来研究极限形状。

Phase transitions, ranging from familiar occurrences such as liquid water freezing into ice to technologically critical phenomena such as transition to superconductivity, are ubiquitous throughout nature, have been an active topic in mathematical and physical research for as long as science has existed, and continue to pose important research challenges. Lattice models, constructed to study natural phase transitions, are probability distributions on subsets of graphs depending on continuous parameters. This research project will study the phase transition of several important lattice models, including (1) the constrained percolation model, which randomly assigns "0" or "1" to each vertex of a graph, satisfying constraints that represent aspects of molecular structure; and (2) the self-avoiding walk, which is a path on a graph visiting each vertex at most once, introduced as a model for long-chain polymers. The work will broaden and deepen the mathematical foundations of the subject, with potential important applications in theoretical physics and chemistry.The investigator aims to develop new theory concerning the phase transition of certain lattice models. Imposing constraints in the percolation model usually makes the model lose stochastic monotonicity, which, in the unconstrained case, is critical to study the phase transition described by the behavior of infinite clusters. One goal of the project is to develop new combinatorial and probabilistic techniques to study the behavior of infinite clusters without using stochastic monotonicity. Enumerating self-avoiding walks is typically difficult due to the non-Markovian structure. The connective constant and exponent of self-avoiding walks are fundamental properties of the underlying graph, yet can be identified for very few graphs. Another goal of this project is to obtain new information about connective constants and exponents for large classes of graphs, which may be achieved by analyzing harmonic functions on graphs. An analog to the central limit theorem in two dimensions is the limit shape behavior of height functions of certain lattice models at criticality, i.e. when the phase transition occurs. The investigator also plans to study the limit shape, using techniques from complex analysis and algebraic geometry.