Zobrazeno 1 - 10
of 128
pro vyhledávání: '"Linyuan Lü"'
Autor:
Dingyi Shi, Fan Shang, Bingsheng Chen, Paul Expert, Linyuan Lü, H. Eugene Stanley, Renaud Lambiotte, Tim S. Evans, Ruiqi Li
Publikováno v:
Communications Physics, Vol 7, Iss 1, Pp 1-13 (2024)
Abstract Clusters or communities can provide a coarse-grained description of complex systems at multiple scales, but their detection remains challenging in practice. Community detection methods often define communities as dense subgraphs, or subgraph
Externí odkaz:
https://doaj.org/article/fbd43d5f3eb146e3b77f36ed70e37f7d
Publikováno v:
Communications Physics, Vol 7, Iss 1, Pp 1-11 (2024)
Abstract Empirical networks exhibit significant heterogeneity in node connections, resulting in a few vertices playing critical roles in various scenarios, including decision-making, viral marketing, and population immunization. Thus, identifying key
Externí odkaz:
https://doaj.org/article/b3ddc6527896468ca95afda501609583
Publikováno v:
Entropy, Vol 26, Iss 3, p 248 (2024)
Diverse higher-order structures, foundational for supporting a network’s “meta-functions”, play a vital role in structure, functionality, and the emergence of complex dynamics. Nevertheless, the problem of dismantling them has been consistently
Externí odkaz:
https://doaj.org/article/28a61d2723144e79ad0893d8c11f900f
Publikováno v:
Communications Physics, Vol 5, Iss 1, Pp 1-12 (2022)
Synchronization is a widespread emergent feature of complex systems. Here, the authors investigate the optimization of synchronization in phase oscillators with higher-order interactions, and find that optimized networks are more homogeneous in the n
Externí odkaz:
https://doaj.org/article/1c2e64e2cef843a1bd527230ef3e09c3
Publikováno v:
Entropy, Vol 25, Iss 10, p 1390 (2023)
Null models are crucial tools for investigating network topological structures. However, research on null models for higher-order networks is still relatively scarce. In this study, we introduce an innovative method to construct null models for hyper
Externí odkaz:
https://doaj.org/article/25b102d30dae48eeb95c71749376e117
Publikováno v:
Communications Physics, Vol 4, Iss 1, Pp 1-9 (2021)
Characterising the structure of real-world complex networks is of crucial importance to understand the emerging dynamics taking place on top of them. In this work the authors investigate the cycle organization of synthetic and real systems, and use s
Externí odkaz:
https://doaj.org/article/8f4dc48982f24f2baeb20cb4f55545e3
Publikováno v:
Entropy, Vol 25, Iss 6, p 916 (2023)
The ability to predict the size of information cascades in online social networks is crucial for various applications, including decision-making and viral marketing. However, traditional methods either rely on complicated time-varying features that a
Externí odkaz:
https://doaj.org/article/9abd0f0032c148cb91124b5bb904cebf
Publikováno v:
Communications Physics, Vol 4, Iss 1, Pp 1-10 (2021)
Identifying potential mechanisms behind opinion formation is key to curb the spread of misinformation and fake news. Here, the authors propose a model of opinion formation on a network of relations of trust and distrust between subjects, and show tha
Externí odkaz:
https://doaj.org/article/70332f367a664c99864061f811fa1004
Autor:
Ginestra Bianconi, Alex Arenas, Jacob Biamonte, Lincoln D Carr, Byungnam Kahng, Janos Kertesz, Jürgen Kurths, Linyuan Lü, Cristina Masoller, Adilson E Motter, Matjaž Perc, Filippo Radicchi, Ramakrishna Ramaswamy, Francisco A Rodrigues, Marta Sales-Pardo, Maxi San Miguel, Stefan Thurner, Taha Yasseri
Publikováno v:
Journal of Physics: Complexity, Vol 4, Iss 1, p 010201 (2023)
The 2021 Nobel Prize in Physics recognized the fundamental role of complex systems in the natural sciences. In order to celebrate this milestone, this editorial presents the point of view of the editorial board of JPhys Complexity on the achievements
Externí odkaz:
https://doaj.org/article/cba57343934c4b2ab1e9deef36e36199
Publikováno v:
Physical Review Research, Vol 4, Iss 4, p 043076 (2022)
Predicting network dynamics based on data, a problem with broad applications, has been studied extensively in the past, but most existing approaches assume that the complete set of historical data from the whole network is available. This requirement
Externí odkaz:
https://doaj.org/article/124660f0ba6548eab032d73d4b9cbf76