Resilience (mathematics)
In
The concept of resilience is particularly useful in systems that exhibit tipping points, whose study has a long history that can be traced back to catastrophe theory. While this theory was initially overhyped and fell out of favor, its mathematical foundation remains strong and is now recognized as relevant to many different systems.[2][3]
History
In 1973, Canadian ecologist
Definition
Mathematically, resilience can be approximated by the inverse of the return time to an equilibrium[6][7][8] given by
where is the maximum eigenvalue of matrix .
The largest this value is, the faster a system returns to the original stable steady state, or in other words, the faster the perturbations decay.[9]
Applications and examples
In ecology, resilience might refer to the ability of the ecosystem to recover from disturbances such as fires, droughts, or the introduction of invasive species. A resilient ecosystem would be one that is able to adapt to these changes and continue functioning, while a less resilient ecosystem might experience irreversible damage or collapse.[10] The exact definition of resilience has remained vague for practical matters, which has led to a slow and proper application of its insights for management of ecosystems.[11]
In
Resilience is an important concept in the study of complex systems, where there are many interacting components that can affect each other in unpredictable ways.[13] Mathematical models can be used to explore the resilience of such systems and to identify strategies for improving their resilience in the face of environmental or other changes. For example, when modelling networks it is often important to be able to quantify network resilience, or network robustness, to the loss of nodes. Scale-free networks are particularly resilient[14] since most of their nodes have few links. This means that if some nodes are randomly removed, it is more likely that the nodes with fewer connections are taken out, thus preserving the key properties of the network.[15]