$(ω_1, ω_2)$-temporal random hyperbolic graphs
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arXiv
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| Autores principales: | , |
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| Formato: | Preprint |
| Publicado: |
2024
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| _version_ | 1866929463646748672 |
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| author | Zambirinis, Sofoclis Papadopoulos, Fragkiskos |
| author_facet | Zambirinis, Sofoclis Papadopoulos, Fragkiskos |
| contents | We extend a recent model of temporal random hyperbolic graphs by allowing connections and disconnections to persist across network snapshots with different probabilities, $ω_1$ and $ω_2$. This extension, while conceptually simple, poses analytical challenges involving the Appell $F_1$ series. Despite these challenges, we are able to analyze key properties of the model, which include the distributions of contact and intercontact durations, as well as the expected time-aggregated degree. The incorporation of $ω_1$ and $ω_2$ enables more flexible tuning of the average contact and intercontact durations, and of the average time-aggregated degree, providing a finer control for exploring the effect of temporal network dynamics on dynamical processes. Overall, our results provide new insights into the analysis of temporal networks and contribute to a more general representation of real-world scenarios. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2403_17440 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | $(ω_1, ω_2)$-temporal random hyperbolic graphs Zambirinis, Sofoclis Papadopoulos, Fragkiskos Physics and Society Statistical Mechanics Social and Information Networks We extend a recent model of temporal random hyperbolic graphs by allowing connections and disconnections to persist across network snapshots with different probabilities, $ω_1$ and $ω_2$. This extension, while conceptually simple, poses analytical challenges involving the Appell $F_1$ series. Despite these challenges, we are able to analyze key properties of the model, which include the distributions of contact and intercontact durations, as well as the expected time-aggregated degree. The incorporation of $ω_1$ and $ω_2$ enables more flexible tuning of the average contact and intercontact durations, and of the average time-aggregated degree, providing a finer control for exploring the effect of temporal network dynamics on dynamical processes. Overall, our results provide new insights into the analysis of temporal networks and contribute to a more general representation of real-world scenarios. |
| title | $(ω_1, ω_2)$-temporal random hyperbolic graphs |
| topic | Physics and Society Statistical Mechanics Social and Information Networks |
| url | https://arxiv.org/abs/2403.17440 |