论文标题
不断变化的环境中的相互信息：非线性相互作用，平衡系统和连续变化的扩散性
Mutual information in changing environments: non-linear interactions, out-of-equilibrium systems, and continuously-varying diffusivities
论文作者
论文摘要
生物化学，生态学和神经科学是旨在描述与复杂，不断变化的环境表现出非平凡耦合的相互作用系统的重要领域的例子。我们最近表明，线性相互作用和切换环境在整个系统的相互信息中分别编码。在这里，我们首先将这些发现概括为一系列非线性相互作用模型。我们发现出现了共同信息中的一个新术语，量化了非线性相互作用和环境变化之间的相互作用，并导致建设性或破坏性信息干扰。此外，我们表明，相对于平衡情况，在平衡环境中出现了较高的互信息。最后，我们将框架推广到不断变化的环境的情况下。我们发现，可以将环境变化精确地映射到有效的空间变化扩散系数中，从而阐明了无均匀培养基中生物物理系统的建模和信息结构的启示。
Biochemistry, ecology, and neuroscience are examples of prominent fields aiming at describing interacting systems that exhibit non-trivial couplings to complex, ever-changing environments. We have recently shown that linear interactions and a switching environment are encoded separately in the mutual information of the overall system. Here, we first generalize these findings to a broad class of non-linear interacting models. We find that a new term in the mutual information appears, quantifying the interplay between non-linear interactions and environmental changes, and leading to either constructive or destructive information interference. Furthermore, we show that a higher mutual information emerges in out-of-equilibrium environments with respect to an equilibrium scenario. Finally, we generalize our framework to the case of continuously varying environments. We find that environmental changes can be mapped exactly into an effective spatially-varying diffusion coefficient, shedding light on modeling and information structure of biophysical systems in inhomogeneous media.
