A closed form for Jacobian reconstruction from time series and its application as an early warning signal in network dynamics

The Jacobian matrix of a dynamical system describes its response to perturbations. Conversely, one can estimate the Jacobian matrix by carefully monitoring how the system responds to environmental noise. We present a closed-form analytical solution for the calculation of a system's Jacobian from a time series. Being able to access the Jacobian enables a broad range of mathematical analyses by which deeper insights into the system can be gained. Here we consider in particular the computation of the leading Jacobian eigenvalue as an early warning signal for critical transitions. To illustrate this approach, we apply it to ecological meta-foodweb models, which are strongly nonlinear dynamical multi-layer networks. Our analysis shows that accurate results can be obtained, although the data demand of the method is still high.

Automated summary

The Jacobian matrix describes a dynamical system's response to perturbations and can be estimated by monitoring the system's response to environmental noise. A closed-form analytical solution for calculating the system's Jacobian from a time series allows for a broad range of mathematical analyses to gain deeper insights into the system. The computation of the leading Jacobian eigenvalue serves as an early warning signal for critical transitions.