{"ID":2852571,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2510.17174","arxiv_id":"2510.17174","title":"Defining the urban \"local\" with low dimensional manifolds of human mobility networks","abstract":"Urban science has largely relied on universal models, rendering the heterogeneous and locally specific nature of cities effectively invisible. Here we introduce a topological framework that defines and detects localities in human mobility networks. We empirically demonstrate that these human mobility network localities are rigorous geometric entities that map directly to geographic localities, revealing that human mobility networks lie on manifolds of dimension \u003c=5. This representation provides a compact theoretical foundation for spatial embedding and enables efficient applications to facility location and propagation modeling. Our approach reconciles local heterogeneity with universal representation, offering a new pathway toward a more comprehensive urban science.","short_abstract":"Urban science has largely relied on universal models, rendering the heterogeneous and locally specific nature of cities effectively invisible. Here we introduce a topological framework that defines and detects localities in human mobility networks. We empirically demonstrate that these human mobility network localities...","url_abs":"https://arxiv.org/abs/2510.17174","url_pdf":"https://arxiv.org/pdf/2510.17174v1","authors":"[\"Hezhishi Jiang\",\"Liyan Xu\",\"Tianshu Li\",\"Jintong Tang\",\"Zekun Chen\",\"Yuxuan Wang\",\"Haoran Liu\",\"Hongmou Zhang\",\"Huanfa Chen\",\"Yu Liu\"]","published":"2025-10-20T05:30:02Z","proceeding":"physics.soc-ph","tasks":"[\"physics.soc-ph\",\"cs.CY\"]","methods":"[]","has_code":false}