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Showing 1–10 of 10 results
Advanced filters: Author: Linyuan Lü Clear advanced filters

  • Identifying influential nodes in networks is important for the understanding of their structure and function, but there are several so far unrelated measures to assess this. Here, the authors unfold relations among knows criteria and construct a family of indices that interpolate between degree and coreness.

    • Linyuan Lü
    • Tao Zhou
    • H. Eugene Stanley
    ResearchOpen Access
    Nature Communications
    Volume: 7, P: 1-7

  • Community detection has been studied for more than 20 years, but a perspective from community center is still missing and most algorithms need global information. The authors propose a linear algorithm based on local information to identify centers and related hierarchical structure for effective community detection, which can enhance clustering vector data as well.

    • Dingyi Shi
    • Fan Shang
    • Ruiqi Li
    ResearchOpen Access
    Communications Physics
    Volume: 7, P: 1-13

  • Key players are a small number of vertices that govern the structure and function of a complex network, and their identification can grant answers in many disciplines. By tapping into quantum information, the authors introduce an entanglement-based metric capable of quantifying the perturbations caused by individual vertices on spectral entropy.

    • Yiming Huang
    • Hao Wang
    • Linyuan Lü
    ResearchOpen Access
    Communications Physics
    Volume: 7, P: 1-11

  • 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 nodes’ degree for undirected interactions, and for directed interactions they are generally structurally asymmetric, but can be symmetric, which differs from the pairwise case.

    • Ying Tang
    • Dinghua Shi
    • Linyuan Lü
    ResearchOpen Access
    Communications Physics
    Volume: 5, P: 1-12

  • 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 such information to define a centrality measure that is more informative than traditional indexes to the end of understanding network dismantling, synchronization, and spreading processes

    • Tianlong Fan
    • Linyuan Lü
    • Tao Zhou
    ResearchOpen Access
    Communications Physics
    Volume: 4, P: 1-9

  • 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 that opinion instability increases with the complexity and size of the system, proposing a candidate mechanism for how trust towards deceptive sources develops.

    • Matúš Medo
    • Manuel S. Mariani
    • Linyuan Lü
    ResearchOpen Access
    Communications Physics
    Volume: 4, P: 1-10