学习布朗运动的非平衡动力学
Learning the Non-Equilibrium Dynamics of Brownian Movies
摘要：
延时显微成像提供了直接访问软和生命系统的动态。在介观尺度下，这种显微镜实验揭示了内在的波动，这可能有热和非平衡起源。这些内在的波动，连同测量噪声，构成了一个重大的挑战，这些“布朗电影”的动力学分析。传统上，分析这种实验数据的方法依赖于追踪嵌入的或内源性的探针。然而，它是在一般不清楚如何选择适当的示踪剂，这是不明显的，特别是在复杂的多体系统，自由度是最有信息的非平衡性质。在这里，我们介绍了一种替代的，跟踪免费的方法，克服了这些困难，通过一个无监督的分析布朗电影。我们开发了一个降维方案，选择基于耗散的模式的基础上，我们随后学习在此基础上的非平衡动力学和估计的熵产生率。此外，我们推断系统中的时间分辨力图，并表明这种方法可扩展到大型系统，从而提供了一个潜在的替代微观力探针。在对我们的方法进行基准测试后，针对最小的双珠模型，我们通过活性生物聚合物凝胶激发的例子说明了其更广泛的适用性。
英文摘要：
Time-lapse microscopy imaging provides direct access to the dynamics of soft and living systems. At mesoscopic scales, such microscopy experiments reveal intrinsic fluctuations, which may have both thermal and non-equilibrium origins. These intrinsic fluctuations, together with measurement noise, pose a major challenge for the analysis of the dynamics of these "Brownian movies". Traditionally, methods to analyze such experimental data rely on tracking embedded or endogenous probes. However, it is in general unclear how to select appropriate tracers; it is not evident, especially in complex many-body systems, which degrees of freedom are the most informative about their non-equilibrium nature. Here, we introduce an alternative, tracking-free approach that overcomes these difficulties via an unsupervised analysis of the Brownian movie. We develop a dimensional reduction scheme that selects a basis of modes based on dissipation, and we subsequently learn the non-equilibrium dynamics in this basis and estimate the entropy production rate. In addition, we infer time-resolved force maps in the system and show that this approach is scalable to large systems, thus providing a potential alternative to microscopic force-probes. After benchmarking our method against a minimal two-beads model, we illustrate its broader applicability with an example inspired by active biopolymer gels.
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