Daniel Ayers et al. have published a new paper paper related to their work in SASIP-WP4:

Supervised machine learning to estimate instabilities in chaotic systems: estimation of local Lyapunov exponents, under review in QJRMS.

Daniel Ayers, Jack Lau, Javier Amezcua, Alberto Carrassi, Varun Ojha.

https://arxiv.org/abs/2202.04944.

Fig.2 (from Ayers et al 2023): A long-time trajectory of the Lorentz63 system coloured by local Lyapunov exponents (LLE) values (top row) shows how LLE values tend to be arranged in the system’s attractor. The bottom row shows the corresponding statistical distribution of the LLEs via histograms; the mean of the LLE values is shown by the dotted orange line. The top panels show the same collection of 25, 000 points. On the other hand, the histograms are generated from the full set of 718, 800 LLEs; note that the vertical axis is plotted in logarithmic scale. The mean (i.e. the corresponding LE) and standard deviation of the LLE values in each column are shown underneath..