Statistical Mechanics of Systems far from Equilibrium

远离平衡系统的统计力学

• 批准号: 0705152
• 负责人: Beate Schmittmann
• 金额: $ 58.5万
• 依托单位: Virginia Polytechnic Institute and State University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-06-15 至 2011-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0705152&HistoricalAwards=false
• 关键词: Statistical; Mechanics; Systems; far; Equilibrium

TECHNICAL SUMMARY:This award supports theoretical research and education in statistical mechanics of systems far from equilibrium. The research studies condensed matter and biological systems that are out of equilibrium by virtue of open boundaries and nontrivial fluxes of energy or matter.This research addresses systems that cannot be properly described within, or as a perturbation about, the traditional equilibrium Boltzmann-Gibbs framework. For such systems there is no comprehensive framework for non-equilibrium phenomena and its formulation is one of the key challenges of modern statistical physics. Cognizant of the larger goal to gain fundamental understanding of the physics of nonequilibrium systems, the researchers will undertake studies ranging from the simplest models to complex living systems and employ analytic and computational approaches. The PIs will study tractable paradigmatic models far from equilibrium, i.e. asymmetric exclusion processes and generalized mass transport models. With some added complexity, these models become the building blocks for a quantitative analysis of an important biological process, namely, protein production from mRNA. This process forms a key component of overall cellular metabolic activity, and understanding the relation between environmental conditions and cellular growth rates constitutes a central problem in the life sciences. Mindful of fundamental issues in non-equilibrium statistical physics, the PIs will exploit the stationary distributions of probability currents (in configuration space) as the basis for a very general classification scheme for non-equilibrium steady states. The PIs' findings from minimal models and application-driven studies will serve as case studies to probe this framework. Its full implications will be explored systematically.NONTECHNICAL SUMMARY:This award supports theoretical research and education in statistical mechanics of systems out of equilibrium. Part of this research lies at the interface of condensed matter physics and biology; it is intrinsically interdisciplinary. The research is motivated by many examples in nature, but addresses condensed matter and biological systems that are out of equilibrium. In particular, living systems undergo the continuous processes that support life because there is a continuous input of energy. Whether we call this food or metabolism or just leave it abstract, it is a key to the development of complex systems and structures or behaviors in systems that are out of equilibrium.This research undertakes studies ranging from the simplest models to complex living systems and employs analytic and computational approaches. A special interest in cellular level repetitious processes, such as protein production by messenger RNA will be studied with mathematical models of assembly line-type activities that have the randomness of nature built into them. Insights can be seen into simple biological processes. Though emphasizing models and biological systems, the researchers have experience connecting this type of transport to a wide range of systems, from traffic flow to information on the Internet. The way the research is structured lends itself well to the education at virtually all levels and this award contributes to the education of the globally competitive workforce next generation.

技术概述：该奖项支持远离平衡系统的统计力学的理论研究和教育。该研究研究了由于开放边界和能量或物质的非平凡通量而处于非平衡状态的凝聚态物质和生物系统。这项研究解决了不能在传统的平衡玻尔兹曼-吉布斯框架内适当描述或作为扰动的系统。对于这样的系统，不存在非平衡现象的综合框架，其表述是现代统计物理学的关键挑战之一。认识到更大的目标是获得对非平衡系统物理的基本理解，研究人员将进行从最简单的模型到复杂的生命系统的研究，并采用分析和计算方法。pi将研究远离平衡的可处理的范式模型，即不对称排斥过程和广义质量输运模型。随着复杂性的增加，这些模型成为一个重要生物过程定量分析的基石，即mRNA产生蛋白质。这一过程构成了整个细胞代谢活动的关键组成部分，理解环境条件和细胞生长速率之间的关系构成了生命科学的核心问题。考虑到非平衡统计物理中的基本问题，pi将利用概率电流的平稳分布（在组态空间中）作为非平衡稳态的非常一般分类方案的基础。pi从最小模型和应用驱动研究中获得的发现将作为案例研究来探索这一框架。我们将系统地探讨其全部影响。非技术概述：该奖项支持非平衡系统统计力学方面的理论研究和教育。这项研究的一部分是在凝聚态物理和生物学的界面；它本质上是跨学科的。这项研究的动机来自于自然界中的许多例子，但涉及的是凝聚态物质和生物系统，它们处于非平衡状态。特别是，生命系统经历了支持生命的连续过程，因为有持续的能量输入。不管我们叫它“食物”还是“新陈代谢”，或者只是把它抽象起来，它都是复杂系统、结构或失衡系统行为发展的关键。本研究的研究范围从最简单的模型到复杂的生命系统，并采用分析和计算方法。对细胞水平重复过程的特殊兴趣，如信使RNA的蛋白质生产，将用具有自然随机性的装配线类型活动的数学模型进行研究。我们可以从简单的生物过程中看到深刻的见解。虽然强调模型和生物系统，但研究人员有经验将这种类型的运输与广泛的系统联系起来，从交通流量到互联网上的信息。该研究的结构方式很好地适用于几乎所有层次的教育，该奖项有助于培养具有全球竞争力的下一代劳动力。