发表机构
Channing Division of Network Medicine, Brigham and Women’s Hospital, Harvard Medical School（查宁网络医学部，布里格姆和妇女医院，哈佛医学院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究证明剔除拓扑因素后，可交换性使边对平均交叉倾向与图无关，并推导无参数理论，揭示网络响应由隐藏的相关性决定。
AI 中文摘要
拓扑与几何在物理网络中密不可分。我们证明，在剔除依赖拓扑的合格边对数后，可交换性使得这些边对的平均交叉倾向完全与图无关，同时拓扑保留在涨落中。我们推导了一个无参数的微观理论，用于描述拓扑与几何耦合时的响应。合成及真实三维网络证实，归一化均值中隐藏的结构存在于决定响应的相关性中。
英文摘要
Topology and geometry are inseparable in physical networks. Here we show that, after factoring out the topology-dependent number of eligible edge pairs, exchangeability makes the mean crossing propensity of those pairs exactly graph independent while preserving topology in fluctuations. We derive a microscopic, parameter-free theory for the response when topology and geometry are coupled. Synthetic and real three-dimensional networks confirm that structure hidden from the normalized mean survives in correlations that determine response.
Comments5 pages, 4 figures
