 In chaos theory, the butterfly effect is the sensitive dependence on initial conditions in which a small change in one state of a deterministic non-linear system can result in large differences in a later state. The term, coined by Edward Lawrence, is derived from the metaphorical example of the details of a tornado the exact time of formation, the exact path taken being influenced by minor perturbations such as a flapping of the wings of a destined butterfly several weeks earlier. Lawrence discovered the effect when he observed that runs of his weather model with initial condition data that was rounded in a seemingly inconsequential manner would fail to reproduce the results of runs with the unrounded initial condition data. The very small change in initial conditions had created a significantly different outcome. Though Lawrence gave the name to the phenomenon, the idea that small causes may have large effects in general and in weather specifically was earlier recognized by French mathematician and engineer Henri Pouacarais and American mathematician and philosopher Norbert Wiener. Edward Lawrence's work placed the concept of instability of the Earth's atmosphere onto a quantitative base handling the concept of instability to the properties of large classes of dynamic systems which are undergoing non-linear dynamics and deterministic chaos. The butterfly effect can also be demonstrated by very simple systems.