论文标题
信息驱动不足动态的预测中的信息驱动的过渡
Information-driven transitions in projections of underdamped dynamics
论文作者
论文摘要
失业不足的系统的低维表示通常提供有见地的掌握和分析性障碍。在这里，我们通过信息预测构建此类表示形式，获得了一个最佳模型，该模型捕获有关观察到的空间轨迹的最多信息。我们表明，在范式系统中，信息损失的最小化驱动了最佳模型参数中不连续过渡的出现。我们的结果对有效的动态表示形式的一般推论方法和揭示基本特性提出了严重警告，从而影响了从生物物理学到降低维度的几个领域。
Low-dimensional representations of underdamped systems often provide insightful grasps and analytical tractability. Here, we build such representations via information projections, obtaining an optimal model that captures the most information on observed spatial trajectories. We show that, in paradigmatic systems, the minimization of the information loss drives the appearance of a discontinuous transition in the optimal model parameters. Our results raise serious warnings for general inference approaches and unravel fundamental properties of effective dynamical representations, impacting several fields, from biophysics to dimensionality reduction.
