Statistical Physics far from Equilibrium

该奖项支持理论研究和教育，以持续努力了解远离热平衡的相互作用多粒子系统的复杂行为。与它们的平衡对应物不同，这些“物理和生物”系统不能用玻尔兹曼和吉布斯的既定框架来描述。一个本质的区别是，这些系统是在与一个以上的水库在这样一种方式，通过系统的非平凡通量持续，即使当他们在时间无关的状态。好的例子包括所有的生物体，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，预测宏观观测的基础微观动力学。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学的基本特征。PI将专注于具有应用于生物系统潜力的模型。完全不对称的简单排它过程将是一个研究热点。 原始模型的许多性质是已知的解析。然而，模型的推广成为定量方法建模细胞中蛋白质生产的基石。这一领域的进展将有助于理解生物运输过程，启发设计和合成蛋白质的可能方法，以及解决非平衡统计物理学中的基本问题的有价值的见解，例如非平凡概率电流环在配置空间中的作用。它很容易在几乎所有各级教育青年科学家。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。非技术性总结该奖项支持远离平衡驱动系统的统计物理学的理论研究和教育。生物提供了一个由许多粒子或部分组成的系统的重要例子，这些粒子或部分远离平衡状态。这项研究的主要目标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寻求一个总体原则，概括了平衡统计力学领域非常成功的基本假设。 这项研究涵盖了广泛的主题，并利用了各种方法：从最简单的数学模型到复杂的生命系统模型，从易于访问的计算机模拟到复杂的场论技术。这项研究的中心焦点在于生物学和材料研究的界面。PI将研究细胞中信使RNA的蛋白质生产。它将被建模为一个类似流水线的活动，并与模拟和强大的工具，在数学和统计学研究。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。鉴于这项研究的主题和方法的范围，它很容易在几乎所有级别的年轻科学家的教育。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.