Life is characterized by a myriad of complex dynamic processes allowing organisms to grow, reproduce, and evolve. Physical approaches for describing systems out of thermodynamic equilibrium have been increasingly applied to living systems, which often exhibit phenomena unknown from those traditionally studied in physics. Spectacular advances in experimentation during the last decade or two, for example, in microscopy, single cell dynamics, in the reconstruction of sub- and multicellular systems outside of living organisms, or in high throughput data acquisition have yielded an unprecedented wealth of data about cell dynamics, genetic regulation, and organismal development. These data have motivated the development and refinement of concepts and tools to dissect the physical mechanisms underlying biological processes. Notably, the landscape and flux theory as well as active hydrodynamic gel theory have proven very useful in this endeavour. Together with concepts and tools developed in other areas of nonequilibrium physics, significant progresses have been made in unraveling the principles underlying efficient energy transport in photosynthesis, cellular regulatory networks, cellular movements and organization, embryonic development and cancer, neural network dynamics, population dynamics and ecology, as well as ageing, immune responses and evolution. Here, we review recent advances in nonequilibrium physics and survey their application to biological systems. We expect many of these results to be important cornerstones as the field continues to build our understanding of life.
Nonequilibrium dynamics and thermodynamics provide the underlying physical mechanism of the perceptual rivalry
Biophysics & Complex System Center, Center of Theoretical Physics, College of Physics, Jilin University（吉林大学物理学院理论物理中心生物物理与复杂系统中心）；Department of Chemistry and of Physics and Astronomy, Stony Brook University（石溪大学化学系及物理与天文学系）
Princeton University（普林斯顿大学）；TU Bergakademie Freiberg（弗莱贝格工业大学）；HTW Dresden（德累斯顿应用科学大学）；King’s College London（伦敦国王学院）；Baylor College of Medicine（贝勒医学院）；Texas Children’s Hospital（德州儿童医院）；Johns Hopkins Bloomberg School of Public Health（约翰斯·霍普金斯布隆伯格公共卫生学院）；Johns Hopkins School of Medicine（约翰斯·霍普金斯医学院）；University of Modena and Reggio Emilia（摩德纳和雷焦艾米利亚大学）
Stochastic Dynamical Structure (SDS) of Nonequilibrium Processes in the Absence of Detailed Balance. II: construction of SDS with nonlinear force and multiplicative noise
非平衡行为中的涌现现象可以用一组随机微分方程很好地描述。受现代生物学中噬菌体λ基因开关的鲁棒性和稳定性研究的启发，我们发现存在一种通用非平衡过程的分类：在随机微分方程的连续描述中，存在四个动力学元素：势函数$ϕ$，摩擦矩阵$ S$，反对称矩阵$ T $和噪声。缺乏细致平衡的一般特征则由$T$精确地表示。对于不动点附近的动力系统，无论其是否稳定，其随机动力系统都是线性的。已经进行了相当完整的分析（Kwon，Ao，Jumless，cond-mat/0506280; PNAS，{ \bf 102}（2005）13029），称为SDS I。一个重要的和持久的问题是存在的势函数与非线性力和乘性噪声，具有良好的局部动力学和全局定态性质。在这里，我们证明了一个动态结构内置到随机微分方程允许我们构建这样一个全局优化势函数。首先，我们提供建筑。其中最重要的组成部分是广义爱因斯坦关系。然后，我们提出了一个近似方案：梯度展开，把每一个订单成线性矩阵方程。这种方法与其他已知的随机处理的一致性将在下一篇论文SDS III中讨论;与统计力学和热力学的明确联系将在即将发表的论文SDS IV中讨论。
