Ford Ian J, Spinney Richard E
Department of Physics and Astronomy, University College London, Gower Street, London WC1E 6BT, United Kingdom.
Phys Rev E Stat Nonlin Soft Matter Phys. 2012 Aug;86(2 Pt 1):021127. doi: 10.1103/PhysRevE.86.021127. Epub 2012 Aug 23.
The stochastic entropy generated during the evolution of a system interacting with an environment may be separated into three components, but only two of these have a non-negative mean. The third component of entropy production is associated with the relaxation of the system probability distribution towards a stationary state and with nonequilibrium constraints within the dynamics that break detailed balance. It exists when at least some of the coordinates of the system phase space change sign under time reversal, and when the stationary state is asymmetric in these coordinates. We illustrate the various components of entropy production, both in detail for particular trajectories and in the mean, using simple systems defined on a discrete phase space of spatial and velocity coordinates. These models capture features of the drift and diffusion of a particle in a physical system, including the processes of injection and removal and the effect of a temperature gradient. The examples demonstrate how entropy production in stochastic thermodynamics depends on the detail that is included in a model of the dynamics of a process. Entropy production from such a perspective is a measure of the failure of such models to meet Loschmidt's expectation of dynamic reversibility.
在与环境相互作用的系统演化过程中产生的随机熵可分为三个分量,但其中只有两个具有非负均值。熵产生的第三个分量与系统概率分布向稳态的弛豫以及动力学中打破细致平衡的非平衡约束有关。当系统相空间的至少一些坐标在时间反演下改变符号,且稳态在这些坐标中不对称时,它就会存在。我们使用在空间和速度坐标的离散相空间上定义的简单系统,详细地针对特定轨迹以及从均值角度说明了熵产生的各个分量。这些模型捕捉了物理系统中粒子漂移和扩散的特征,包括注入和移除过程以及温度梯度的影响。这些例子展示了随机热力学中的熵产生如何取决于过程动力学模型中所包含的细节。从这样的角度来看,熵产生是衡量此类模型未能满足洛施密特对动态可逆性期望的一种度量。