Network resilience
By Xueming Liu, Daqing Li, Manqing Ma, Boleslaw K. Szymanski, H. Eugene Stanley, Jianxi Gao. Physics reports, 2020
162 citations recorded by the source corpus.
Many systems on our planet are known to shift abruptly and irreversibly from one state to another when they are forced across a "tipping point," such as mass extinctions in ecological networks, cascading failures in infrastructure systems, and social convention changes in human and animal networks. Such a regime shift demonstrates a system's resilience that characterizes the ability of a system to adjust its activity to retain its basic functionality in the face of internal disturbances or external environmental changes. In the past 50 years, attention was almost exclusively given to low dimensional systems and calibration of their resilience functions and indicators of early warning signals without considerations for the interactions between the components. Only in recent years, taking advantages of the network theory and lavish real data sets, network scientists have directed their interest to the real-world complex networked multidimensional systems and their resilience function and early warning indicators. This report is devoted to a comprehensive review of resilience function and regime shift of complex systems in different domains, such as ecology, biology, social systems and infrastructure. We cover the related research about empirical observations, experimental studies, mathematical modeling, and theoretical analysis. We also discuss some ambiguous definitions, such as robustness, resilience, and stability.
Subfields: Environmental Engineering, Global and Planetary Change, Statistical and Nonlinear Physics
View Paper: https://www.semanticscholar.org/paper/fd47bc8529b4949d3af86878d7df6a97307790f2
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Citations in the corpus
- Task‐specific topology of brain networks supporting working memory and inhibition (2024, background): “By providing additional routes for neural signaling, weak connections may endow the network with enhanced resilience against localized disruptions, ensuring sustained cognitive function even in the face of potential perturbations (X. Liu et al., 2022; Nassi & Callaway, 2009).”