Statistical Physics far from Equilibrium

技术总结该奖项支持理论研究和教育，以继续努力了解远离热平衡的多粒子系统相互作用的复杂行为。与它们的平衡对应系统不同，这些系统“无论是物理的还是生物的”，都不能用博尔兹曼和吉布斯的成熟框架来描述。一个根本的区别是，这些系统与不止一个水库接触的方式是，即使它们处于与时间无关的状态，通过这些系统的非平凡的通量也会持续存在。很好的例子包括所有活着的有机体，地球作为一个生态系统，以及我们现代基础设施的许多方面。关键的挑战是设计一个可靠的理论框架，从潜在的微观动力学预测宏观可观测。目前还缺乏非平衡统计力学的总体框架。PI将研究最不复杂的模型，其中包括远离平衡物理的基本特征。PI将侧重于具有应用于生物系统的潜力的模型。完全不对称的简单排斥过程将成为研究的重点。原始模型的许多性质在解析上是已知的。然而，该模型的泛化成为了对细胞中蛋白质生产进行建模的定量方法的基础。这一领域的进展将有助于理解生物传输过程，启发可能的方法来设计和合成蛋白质，以及为解决非平衡统计物理中的基本问题提供有价值的见解，例如非平凡概率电流环在位形空间中的作用。鉴于这项研究的主题和方法的范围，它很容易为几乎所有水平的年轻科学家提供教育。通过这种方式，该奖项有助于培养下一代具有全球竞争力的劳动力。非技术总结该奖项支持远离平衡的系统统计物理的理论研究和教育。生物提供了一个重要的例子，说明由许多粒子或部分组成的系统远离被称为平衡的平衡状态。这项研究的主要目的是阐明材料和其他远离平衡的系统的理论和概念框架的基础。PI寻求一个最重要的原则，该原则概括了平衡统计力学领域极其成功的基本假设。这项研究涵盖了广泛的主题，并采用了各种方法：从最简单的数学模型到复杂生命系统的模型，从易于使用的计算机模拟到复杂的领域理论技术。这项研究的一个中心焦点是生物学和材料研究的交界点。PI将研究细胞中信使RNA产生的蛋白质。它将被建模为一个类似装配线的活动，并利用模拟和强大的数学和统计工具进行研究。这项研究将应用所获得的见解来调查更广泛的交通系统，从交通流量到互联网上的信息。考虑到这项研究的主题和方法的范围，它很容易适用于几乎所有级别的青年科学家的教育。通过这种方式，该奖项有助于培养下一代具有全球竞争力的劳动力。

TECHNICAL SUMMARYThis award supports theoretical research and education in a continuing effort to understand the complex behavior in interacting many-particle systems driven far from thermal equilibrium. Unlike their equilibrium counterparts, these systems "both physical and biological" cannot be described by the well established framework of Boltzmann and Gibbs. One essential difference is that these systems are in contact with more than one reservoir in such a way that nontrivial fluxes through the systems persist, even when they are in time-independent states. Good examples include all living organisms, the earth as an ecosystem, and many aspects of our modern infrastructure. The key challenge is to devise a reliable theoretical framework which predicts macroscopic observables from the underlying microscopic dynamics. An overarching framework for non-equilibrium statistical mechanics is lacking. The PIs will study the least complex models which include essential characteristics of far-from-equilibrium physics. The PIs will focus on models with the potential for applications to biological systems. The totally asymmetric simple exclusion process will be a focus of study. Many properties of the original model are known analytically. However, generalizations of the model become the building blocks for a quantitative approach to modeling protein production in a cell. Progress in this field will contribute to understanding biological transport processes, inspire possible ways to design and synthesize proteins, as well as to valuable insights for addressing fundamental issues in non-equilibrium statistical physics, such as the role of non-trivial probability current loops in configuration space.Given the range of topics and methods in this research, it lends itself readily to the education of young scientists at virtually all levels. In this way, this award contributes to the training of the next generation of a globally competitive workforce.NONTECHNICAL SUMMARYThis award supports theoretical research and education in statistical physics of systems driven far from equilibrium. Living things provide an important example of a system composed of many particles or parts that is far from the balanced state known as equilibrium. The main goal of this research is to elucidate the foundations of a theoretical and conceptual framework for materials and other systems that are far from equilibrium. The PIs seek an overarching principle which generalizes the extremely successful fundamental hypothesis of the field of equilibrium statistical mechanics. This research covers a wide range of topics and exploits a variety of methods: from the simplest mathematical models to models of complex living systems and from readily accessible computer simulations to sophisticated field theoretic techniques. A central focus of this research lies at the interface of biology and materials research. The PIs will study protein production by messenger RNA in cells. It will be modeled as an assembly-line-like activity and studied with both simulations and powerful tools in mathematics and statistics. This research will apply the insights gained to investigate a wider range of transport systems, from traffic flow to information on the Internet. Given the range of topics and methods in this research, it lends itself readily to the education of young scientists at virtually all levels. In this way, this award contributes to the training of the next generation of a globally competitive workforce.