JPhys Complexity特刊征稿|Focus on Network Robustness

特刊详情

客座编辑

• Gareth Baxter，葡萄牙阿威罗大学
• 董高高，江苏大学
• Jan Korbel，奥地利复杂性科学中心
• 刘雪明，华中科技大学

主题范围

Representation in terms of complex networks has proven to be a powerful approach to deal with the heterogeneity and small- and large-scale patterns of interactions in many complex systems. It has provided a common toolset applicable to an incredibly diverse set of applications, including the dynamics of ecosystems, the spread of information, social relationships, epidemics, transport and mobility, financial networks, the internet and world wide web, gene regulation and the functioning of the brain.

One common theme linking the study of many of these systems is the need to understand their robustness. Questions of how resilient systems are against damage, how they can recover from damage and how they can best be protected against failure are transversal.

Contributions on this perennial topic range from the foundation provided by the theory of network percolation to data-driven studies analysing the robustness of real-world systems, to analysis and algorithms for the optimization of robustness. With the expansion of network theory to account for higher order interactions and structures, the emergence of AI tools and appearance of new applications, there remain many interesting open questions in this area.

This focus collection aims to highlight the latest research covering all aspects of robustness in complex networks; topics which may be addressed include, but are not limited to:

• Network robustness of financial and economic networks
• Network robustness of traffic, logistics, communications and infrastructure networks
• Network robustness of biological, climate and other natural networks
• Percolation and critical phenomena of complex networks
• Robustness in multilayer and interdependent networks
• Hypergraph and simplicial network robustness
• Robustness in temporal and adaptive networks
• Cascading failures and systemic risk in networks
• Early-warning signals and critical transitions in networked systems
• Theoretical approaches to robustness
• Network dismantling, vulnerability analysis and attack strategies
• Modelling of network robustness
• Robustness analysis
• Network recovery
• Optimisation of resilience, recovery and stability
• Application of AI and ML for network robustness
• Quantum network robustness

投稿流程

特刊文章与JPhys Complexity期刊常规文章遵循相同的审稿流程和内容标准，并采用同样的投稿模式。

有关准备文章及投稿的详细信息，可以参阅IOPscience页面的作者指南。

作者可登入期刊主页进行在线投稿，在“文章类型”中选择“特刊文章”，并在“选择特刊”的下拉框中选择“Focus on Network Robustness”。

投稿截止日期：2026年11月30日。