Institut für Physik, Johannes Gutenberg-Universität Mainz, Staudingerweg 7-9, 55128 Mainz, Germany.
J Chem Phys. 2021 Dec 21;155(23):230901. doi: 10.1063/5.0070922.
Numerical computations have become a pillar of all modern quantitative sciences. Any computation involves modeling-even if often this step is not made explicit-and any model has to neglect details while still being physically accurate. Equilibrium statistical mechanics guides both the development of models and numerical methods for dynamics obeying detailed balance. For systems driven away from thermal equilibrium, such a universal theoretical framework is missing. For a restricted class of driven systems governed by Markov dynamics and local detailed balance, stochastic thermodynamics has evolved to fill this gap and to provide fundamental constraints and guiding principles. The next step is to advance stochastic thermodynamics from simple model systems to complex systems with tens of thousands or even millions of degrees of freedom. Biomolecules operating in the presence of chemical gradients and mechanical forces are a prime example for this challenge. In this Perspective, we give an introduction to isothermal stochastic thermodynamics geared toward the systematic multiscale modeling of the conformational dynamics of biomolecular and synthetic machines, and we outline some of the open challenges.
数值计算已经成为所有现代定量科学的支柱。任何计算都涉及建模——即使在很多情况下这一步并不明确——而且任何模型都必须忽略细节，同时保持物理准确性。平衡统计力学指导着服从详细平衡的动力学模型和数值方法的发展。对于远离热平衡的系统，这种普遍的理论框架是缺失的。对于一类由马尔可夫动力学和局部详细平衡控制的受限驱动系统，随机热力学已经发展起来，以填补这一空白，并提供基本的约束和指导原则。下一步是将随机热力学从简单的模型系统推进到具有成千上万个甚至数百万个自由度的复杂系统。在化学梯度和机械力作用下工作的生物分子就是这一挑战的一个主要例子。在这篇观点文章中，我们介绍了等温热力学，旨在对生物分子和合成机器的构象动力学进行系统的多尺度建模，并概述了一些开放的挑战。
