Systems are said to be linear if the superposition principle holds. This principle states that the net result of two or more inputs at given times with a system is equal to the net result of those inputs at another time. The simple diagrammatic figure that is often used to represent this is the waveform. Nonlinear systems diverge from this neat progression in interesting and dynamical ways. Ladyman, Lambert, and Weisner (“What is a Complex System“, 2011) make special note of the divergence between microstate linearity and macro-state nonlinear dynamic systems derived from small perturbations in the microstate progression (the classic butterfly example of chaos mathematics). Despite this divergence however, linear descriptions may often be used to approximately model the conditions of macrostate entities, even if the resulting model is not strictly true. Because of this, nonlinearity is not a necessary condition for complex systems. In addition, the fact that simple systems, like a pendulum, can exhibit nonlinear dynamics, it is also not a sufficient condition. Nonetheless, they believe that nonlinear dynamics may play a role in most complex systems, in conjunction with, or as a subset of some other conditions, and so consider it a related property.