发表机构
Chengdu Academy of Educational Sciences（成都教育科学研究院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出利用有向可见事件间的等待时间分布，在无需观测逆向跃迁的条件下重建边界动力学，并给出总熵产生的严格下界，仅需一个跨越有向环即可识别完整马尔可夫生成器。
AI 中文摘要
实验通常仅检测选定的跃迁，导致潜在的状态动力学和耗散隐藏。我们证明，有向可见事件之间的等待时间分布可以在不观测每个检测跃迁的逆向过程的情况下重建边界动力学。在简单的源-目标闭合条件下，这些分布能够确定可见速率以及连接观测状态的隐藏偏移，从而给出总熵产生的严格下界，当逆向事件可用时，该下界优于标准等待时间估计。值得注意的是，仅观测一个跨越的有向环就足以识别完整的马尔可夫生成器，即使所有逆向环边和其他微观跃迁仍然未被观测到。
英文摘要
Experiments often detect only selected transitions, leaving the underlying state dynamics and dissipation hidden. We show that waiting-time distributions between directed visible events can reconstruct the boundary dynamics without observing the reverse of every detected transition. Under a simple source-target closure condition, they determine visible rates and the hidden excursions connecting observed states, yielding a rigorous lower bound on total entropy production that improves the standard waiting-time estimate when reverse events are available. Remarkably, observing only a spanning directed cycle is sufficient to identify the full Markov generator, even when all reverse cycle edges and other microscopic transitions remain unseen.
Comments5 pages, 3 figures. Comments are welcome
