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Geometry of Physical Models Governed by Diffusion

扩散控制的物理模型的几何

基本信息

批准号：
1812009
负责人：
Eviatar Procaccia
金额：
$ 18万
依托单位：
Texas A&M University
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2018
资助国家：
美国
起止时间：
2018-06-01 至 2021-09-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1812009&HistoricalAwards=false
关键词：
Geometry Physical Models Governed Diffusion

项目摘要

Over the past decades probability theory has had tremendous success in elucidating scaling limits and large-scale phenomena. However, systems that have no apparent scaling limit are abundant in both the physical and life sciences, and there is practical need to better understand such systems. This research project aims to advance understanding of such systems by studying models augmented with additional symmetries that share the local behavior of the classical disordered systems under study. Graduate students and postdoctoral associates will receive training through involvement in the research. The topics under study in this project divide into three subareas: (1) stationary diffusion limited aggregation (DLA) and Hastings-Levitov models, (2) DLA in a wedge, and (3) chemical distance in random interlacements. These models are of interest for statistical mechanics and mathematical physics. They share the features of being generated by diffusion or the harmonic measure, and of attempting to grasp the nature of a physical phenomenon that is not amenable more classical models in the field, such as DLA or Bernoulli percolation. The methods to be employed borrow ideas and tools from various mathematical disciplines, including complex analysis, harmonic analysis, differential equations, and ergodic theory.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.

在过去的几十年里，概率论在阐明尺度极限和大尺度现象方面取得了巨大的成功。然而，在物理和生命科学中，没有明显尺度限制的系统是丰富的，并且实际上需要更好地理解这样的系统。该研究项目旨在通过研究增加了额外对称性的模型来促进对此类系统的理解，这些对称性与所研究的经典无序系统的局部行为相同。研究生和博士后助理将通过参与研究接受培训。本计画的研究主题分为三个子领域：（1）固定扩散限制聚集（DLA）与Hastings-Levitov模型，（2）楔形中的DLA，以及（3）随机交错中的化学距离。这些模型是统计力学和数学物理的兴趣。它们都具有由扩散或调和测度产生的特征，并试图把握一种物理现象的本质，这种物理现象不适合该领域的经典模型，如DLA或伯努利渗流。所采用的方法借用了各种数学学科的思想和工具，包括复分析、调和分析、微分方程和遍历理论。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。