Surfacic networks
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866915251091406848 |
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| author | Barthelemy, Marc Boeing, Geoff Chiarada, Alain Webster, Chris |
| author_facet | Barthelemy, Marc Boeing, Geoff Chiarada, Alain Webster, Chris |
| contents | Surfacic networks are structures built upon a two-dimensional manifold. Many systems, including transportation networks and various urban networks, fall into this category. The fluctuations of node elevations imply significant deviations from typical plane networks and require specific tools to understand their impact. Here, we present such tools, including lazy paths that minimize elevation differences, graph arduousness which measures the tiring nature of shortest paths, and the excess effort, which characterizes positive elevation variations along shortest paths. We illustrate these measures using toy models of surfacic networks and empirically examine pedestrian networks in selected cities. Specifically, we examine how changes in elevation affect the spatial distribution of betweenness centrality. We also demonstrate that the excess effort follows a non-trivial power law distribution, with an exponent that is not universal, which illustrates that there is a significant probability of encountering steep slopes along shortest paths, regardless of the elevation difference between the starting point and the destination. These findings highlight the significance of elevation fluctuations in shaping network characteristics. Surfacic networks offer a promising framework for comprehensively analyzing and modeling complex systems that are situated on or constrained to a surface environment. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_02484 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Surfacic networks Barthelemy, Marc Boeing, Geoff Chiarada, Alain Webster, Chris Physics and Society Disordered Systems and Neural Networks Statistical Mechanics Surfacic networks are structures built upon a two-dimensional manifold. Many systems, including transportation networks and various urban networks, fall into this category. The fluctuations of node elevations imply significant deviations from typical plane networks and require specific tools to understand their impact. Here, we present such tools, including lazy paths that minimize elevation differences, graph arduousness which measures the tiring nature of shortest paths, and the excess effort, which characterizes positive elevation variations along shortest paths. We illustrate these measures using toy models of surfacic networks and empirically examine pedestrian networks in selected cities. Specifically, we examine how changes in elevation affect the spatial distribution of betweenness centrality. We also demonstrate that the excess effort follows a non-trivial power law distribution, with an exponent that is not universal, which illustrates that there is a significant probability of encountering steep slopes along shortest paths, regardless of the elevation difference between the starting point and the destination. These findings highlight the significance of elevation fluctuations in shaping network characteristics. Surfacic networks offer a promising framework for comprehensively analyzing and modeling complex systems that are situated on or constrained to a surface environment. |
| title | Surfacic networks |
| topic | Physics and Society Disordered Systems and Neural Networks Statistical Mechanics |
| url | https://arxiv.org/abs/2501.02484 |