发表机构
Institute of Science Tokyo（东京科学大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究提出基于引力的家庭交换模型，将城市通勤视为粒子系统，发现其具有玻璃态动力学特征，并通过模拟验证了最小物理机制可重建复杂城市现实。
AI 中文摘要
本研究建立了宏观城市通勤流与热平衡之间的联系。利用日本六个城市一年内约3000万条记录的流动性数据，我们提出了基于引力的家庭交换模型（GHSM）。该模型将通勤者视为相互作用的粒子，将Metropolis动力学应用于城市通勤。在此框架下，总通勤时间决定系统能量，而温度控制流动性对成本节约的响应强度。因此，城市通勤可以通过可评估的自由能进行分析，并类似于物质物理系统进行模拟。最大熵双重约束引力模型作为稳态。我们发现居住动力学表现出玻璃态特征。通过校准到观测数据，我们揭示系统表现出动力学约束模型的迹象，特别是老化、滞后和接近平衡时的冻结。从任意状态初始化的模拟收敛到经验起点-终点矩阵。这表明最小物理机制可以重建复杂的城市现实。
英文摘要
This research establishes a connection between macroscopic urban commuting flows and thermal equilibrium. Using mobility data from around 30 million records across six Japanese cities over one year, we introduce the Gravity-based Home Swapping Model (GHSM). This model applies Metropolis dynamics to urban commuting by treating individuals as interacting particles. Within this framework, total commuting time dictates the system energy, and temperature controls how strongly mobility responds to cost savings. Consequently, urban commuting can be analyzed through an evaluable free energy and simulated similarly to physical systems of matter. The maximumentropy doubly constrained gravity model serves as the stationary state. We find that the residential dynamics exhibit glassy characteristics. Through calibration to observed data, we reveal that the system demonstrates signatures of kinetically constrained models, specifically ageing, hysteresis, and freezing near equilibrium. Simulations initialized from arbitrary states converge to empirical origin-destination matrices. This demonstrates that minimal physical mechanisms can reconstruct complex urban realities.
