Nonlinear Partial Differential Equations and Applications

非线性偏微分方程及其应用

• 批准号: 0901802
• 负责人: Panagiotis Souganidis
• 金额: $ 50.8万
• 依托单位: University of Chicago
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-01 至 2014-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0901802&HistoricalAwards=false
• 关键词: Nonlinear; Partial; Differential; Equations; Applications

SouganidisThe modeling of multi-scale phenomena necessitates the use of random media (periodicity is a rather restrictive structure for many applications) and requires the study of averaged (mesoscopic and macroscopic) behaviors. For complex phenomena, it is also very common to have only \statistical? (random) and not \exact? (deterministic) information. In addition, incorporating the fluctuations of several physical quantities leads to equations with \singular? (white noise type) dependence on some of the variables. In this context, random homogenization and stochastic pde become the natural mathematical objects. The randomness is associated with singular dependence on the state variables and lack of compactness both giving rise to challenging mathematical problems. Overcoming them requires the development of new methods and techniques. Viscosity solutions of nonlinear ¯rst- and second-order pde have become a classical tool for the study of many applications. It is therefore important to improve the understanding of their qualitative properties. In biology, recent experiments at the molecular scale have led to new sophisticated mathematical models. Novel tools and ideas are needed to study these problems further and to identify all the relevant regimes/scales of the parameters affecting the experimentally observed behavior. The PI proposes to continue his program to develop methods to study nonlinear deterministic and stochastic pde arising in continuum and statistical physics, biology, engineering, etc.. The emphasis of the proposal is on (i) the development of theories for weak (stochastic viscosity) solutions of fully nonlinear, (degenerate) parabolic stochastic pde, and the homogenization of nonlinear, parabolic/elliptic and hyperbolic pde in spatiotemporal random media, (ii) the study of problems related to viscosity solutions (rates of convergence, averaging, large deviations in infinite dimensions, etc.), and (iii) the analysis of models for motor and concentration effects in mathematical biology. First- and second-order, stochastic pde and stochastic homogenization arise in models for a wide variety of phenomena and applications including turbulence, phase transitions and front propagation in random media with/out random velocities, nucleations in physics, macroscopic limits of particle systems, stochastic control theory, stochastic control with partial observations, financial mathematics, etc.. The theory of stochastic viscosity solutions is important. It allows for the study of a completely new class of fully nonlinear stochastic pde. As the theory develops further, it is expected that it will play a crucial role in applied areas by providing the necessary tools to analyze previously intractable models. There has been resurgence of interest in homogenization in random media. The novel tools proposed to be developed are expected to become the standard methodology in the field. Providing a unified (analytic) treatment, based on viscosity solutions, to a class of large deviation problems in infinite dimensions will lead to a better understanding of an important area with applications to particle systems, random matrices, phase transitions, etc.. In mathematical biology, the proposed work is expected to enhance the understanding of concrete phenomena like bio-motor behavior and concentration effects.

Souganidis 多尺度现象的建模需要使用随机介质（周期性对于许多应用来说是一个相当限制性的结构），并且需要研究平均（介观和宏观）行为。对于复杂的现象，仅具有“统计”也是很常见的？ （随机）而不是\精确？ （确定性）信息。此外，结合几个物理量的涨落可以得到带有 \singular? 的方程。 （白噪声类型）依赖于一些变量。在这种背景下，随机均质化和随机偏微分方程成为自然的数学对象。随机性与对状态变量的奇异依赖性和缺乏紧凑性相关，两者都会引起具有挑战性的数学问题。克服它们需要开发新的方法和技术。非线性一阶和二阶偏微分方程的粘度解已成为许多应用研究的经典工具。因此，提高对其定性特性的理解非常重要。在生物学中，最近的分子尺度实验产生了新的复杂数学模型。需要新的工具和想法来进一步研究这些问题，并确定影响实验观察行为的参数的所有相关机制/尺度。 PI 建议继续开发研究连续介质和统计物理、生物学、工程学等领域中出现的非线性确定性和随机偏微分方程的方法。该提案的重点是 (i) 发展完全非线性、（简并）抛物线随机偏微分方程的弱（随机粘性）解的理论，以及非线性、抛物线/椭圆和 时空随机介质中的双曲偏微分方程，(ii) 研究与粘度解相关的问题（收敛率、平均、无限维度中的大偏差等），以及 (iii) 数学生物学中运动和浓度效应模型的分析。 一阶和二阶、随机偏微分方程和随机均质化出现在各种现象和应用的模型中，包括没有/没有随机速度的随机介质中的湍流、相变和前向传播、物理学中的成核、粒子系统的宏观极限、随机控制理论、部分观测的随机控制、金融数学等。随机粘度解的理论是 重要的。它允许研究一类全新的完全非线性随机偏微分方程。随着该理论的进一步发展，预计它将通过提供必要的工具来分析以前难以处理的模型，从而在应用领域发挥至关重要的作用。人们对随机介质的同质化重新产生了兴趣。拟议开发的新颖工具预计将成为该领域的标准方法。基于粘度解决方案，对无限维度的一类大偏差问题提供统一（分析）处理，将有助于更好地理解粒子系统、随机矩阵、相变等重要领域的应用。在数学生物学中，拟议的工作有望增强对生物运动行为和浓度效应等具体现象的理解。