On the susceptibility of numerical methods to computational chaos and superstability

In the present study, the susceptibility of the forward and the backward Euler methods to computational chaos and superstability is investigated via the means of both a theoretical analysis and numerical experiments. A linear stability analysis of the fixed points and the periodic orbits of the maps induced by these methods asserts that, for large enough time-steps δt, these maps undergo bifurcations and as result the acquired solutions are spurious. More specifically, it is shown that the backward Euler method suppresses chaotic behavior, whereas the forward Euler renders all linearly stable fixed points and periodic orbits of its induced map linearly unstable. Numerical experiments that illustrate the validity of the theoretical analysis are also presented and discussed. For the forward Euler method, in particular, the computation of bifurcation diagrams, the Maximum Lyapunov exponent and the Kolmogorov-Sinai entropy suggest that it can engender computational chaos