Statistical Mechanics of Systems far from Equilibrium

该奖项支持远离平衡系统的统计力学的理论研究和教育。该研究主要研究由于开放边界和非平凡的能量或物质流而处于非平衡状态的凝聚态物质和生物系统。该研究涉及无法在传统平衡Boltzmann-Gibbs框架内正确描述或作为其扰动的系统。对于这样的系统，没有全面的框架来描述非平衡现象，它的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学的基本理解，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将研究远离平衡的易处理的范式模型，即不对称排斥过程和广义质量传输模型。随着一些额外的复杂性，这些模型成为定量分析一个重要的生物过程，即从mRNA的蛋白质生产的基石。这个过程形成了整体细胞代谢活动的关键组成部分，了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中心问题。考虑到非平衡统计物理学中的基本问题，PI将利用概率流（在配置空间中）的平稳分布作为非平衡稳态的非常一般的分类方案的基础。PI从最小模型和应用驱动的研究中得出的结果将作为探索这一框架的案例研究。它的全部含义将被系统地探讨。非技术性总结：该奖项支持理论研究和教育系统的统计力学的平衡。这项研究的一部分在于凝聚态物理学和生物学的界面;它本质上是跨学科的。这项研究的动机是自然界中的许多例子，但解决了凝聚态物质和生物系统失去平衡的问题。特别是，生命系统经历了支持生命的连续过程，因为有能量的连续输入。无论我们称之为食物或代谢或只是让它抽象，它是一个关键的复杂系统的发展和结构或系统中的行为是不平衡的。本研究承担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别兴趣，例如信使RNA的蛋白质生产，将使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。我们可以看到简单的生物过程。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交通工具连接到广泛的系统，从交通流量到互联网上的信息。该研究的结构方式非常适合几乎所有级别的教育，该奖项有助于下一代具有全球竞争力的劳动力的教育。

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.