AMC-SS: Mathematical and Computational in Nonequilibrium Statistical Mechanics.

AMC-SS：非平衡统计力学中的数学和计算。

• 批准号: 0605058
• 负责人: Luc Rey-Bellet
• 金额: --
• 依托单位: University of Massachusetts Amherst
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-07-15 至 2010-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0605058&HistoricalAwards=false
• 关键词: AMC; SS; Mathematical; Computational; Nonequilibrium

Luc Rey-Bellet works in several directions in statistical mechanics,both in equilibrium and non-equilibrium. (a) The construction and theergodic properties of stationary states for stochastic partialdifferential equations arising from a model of a nonlinearKlein-Gordon equation coupled to one or several heat reservoirs. (b)The validity of the fluctuation theorem for entropy production in someclass of non-uniformly hyperbolic systems, such as billiards. Thisinvolves the development of large deviations techniques for suchsystems. (c) The validity of the fluctuation theorem for the entropyproduction in classical and quantum open systems. (d) The developmentof higher-order coarse-graining numerical schemes for Monte-Carlomethods. Many fundamental problems in non-equilibrium statisticalmechanics remain poorly understood, both at the conceptual andmathematical level: for example the characterization of non-equilibriumstationary states of driven open systems. The fluctuation theorem ofGallavotti and Cohen is a new universal property of these states andits study in various systems (deterministic, random and quantum) willbe one of the main theme in the work of the investigator. Multiscalenumerical methods and the general question of extracting the relevantdegrees of freedom out of complex systems is a problem of paramountimportance in modern applied mathematics. The investigator proposesto use probabilistic techniques from statistical mechanics (clusterexpansion and renormalization group) to develop efficient numericalschemes for the coarse-graining of Monte-Carlo methods. The proposalof the investigator, besides its theoretical aspects, has a number ofapplications to various concrete physical models. These applicationsare integrated (via numerical or analytical work) into graduateresearch projects. The project involves several collaborations withresearchers in U.S. institutions and abroad. The project also helps tothe dissemination of modern mathematical tools, in particularprobabilistic ones, into applied sciences.The field of statistical mechanics is the physical and mathematicaltheory which attempts to link the microscopic and macroscopic worlds.The microscopic world, the world of atoms and molecules, is describedby the laws of Newtonian or Quantum mechanics which involve a hugenumber of equations. The macroscopic world on the contrary is usuallydescribed by a few parameters or equations, such as pressure,temperature, electrical and thermal conductivity, etc... Thisreduction comes from the fact that a very large number of particles,seen from through macroscopic lenses, behave in a very regularfashion. For example, in a well isolated room, the temperaturethroughout the room will be nearly constant. Another example is apiece of metal heated at one end and cooled at the other end: therewill be a flow of energy from the hot part to the cold part but(almost) never in the opposite direction. This phenomena are similar,both in spirit and in mathematical terms to the following: if one throws an unbiased coin very many times then the proportion of headwill be extremely close to one half and (almost) never exhibitsignificant deviations. It turns out that to study this typicalbehavior it is very useful to study and characterize the rare eventscorresponding to untypical behavior, i.e., "large deviations". Havinga detailed understanding of the atypical behavior of a very largenumber of particles is in fact the clue to a fundamental understandingof what is really typical. Theses ideas, which go back to the foundingfathers of physics and probability theory, and their implementationsin various physical situations form the core of the proposal.

Luc Rey-Bellet在统计力学的几个方向上工作，包括平衡和非平衡。(a)由耦合到一个或几个热源的非线性klein - gordon方程模型引起的随机偏微分方程的定态构造及其循环性质。(b)涨落定理在一类非均匀双曲系统（如台球）中熵产生的有效性。这涉及到为这样的系统开发大偏差技术。(c)涨落定理在经典和量子开放系统中熵产生的有效性。(d)蒙特卡罗方法的高阶粗粒数值格式的发展。非平衡统计力学中的许多基本问题在概念和数学层面上仍然知之甚少：例如，驱动开放系统的非平衡稳态的表征。gallavotti和Cohen的涨落定理是这些状态的一个新的普遍性质，它在各种系统（确定性、随机和量子）中的研究将是研究者工作的主题之一。多尺度数值方法和从复杂系统中提取相关自由度的一般问题是现代应用数学中的一个极为重要的问题。研究者建议使用统计力学中的概率技术（聚类展开和重整化群）来开发蒙特卡罗方法粗粒度化的有效数值方案。研究者的建议，除了其理论方面，有许多应用于各种具体的物理模型。这些应用程序（通过数值或分析工作）集成到研究生的研究项目中。该项目涉及与美国机构和国外研究人员的几项合作。该项目还有助于将现代数学工具，特别是概率数学工具推广到应用科学领域。统计力学领域是试图将微观世界和宏观世界联系起来的物理和数学理论。微观世界，原子和分子的世界，是由牛顿或量子力学定律描述的，其中涉及大量的方程。宏观世界则相反，通常用一些参数或方程来描述，如压力、温度、电导率和导热率等。这种减少来自于这样一个事实，即从宏观的角度来看，大量的粒子以一种非常规则的方式运动。例如，在一个隔离良好的房间里，整个房间的温度几乎是恒定的。另一个例子是一块金属在一端加热，在另一端冷却：能量会从热的部分流向冷的部分，但（几乎）从来没有相反的方向。这一现象在精神上和数学上都与以下现象相似：如果一个人多次投掷一枚无偏硬币，那么正面的比例将非常接近一半，并且（几乎）从未表现出明显的偏差。事实证明，研究这种典型行为，研究和表征与非典型行为对应的罕见事件，即“大偏差”，是非常有用的。对大量粒子的非典型行为有详细的了解，实际上是对什么是真正典型的基本理解的线索。这些思想可以追溯到物理学和概率论的创始人，以及它们在各种物理情况下的实现构成了该建议的核心。