
At a tipping point, the system state can change slowly or abruptly - for example, when the complete melting of a glacier can no longer be stopped.
It is an essential question for scientists in every field: How can we predict and influence changes in a networked system? "In biology, one example is the modelling of coordinated neuron activity," says Christian Kühn, professor of multiscale and stochastic dynamics at TUM. Models of this kind are also used in other disciplines, for example when studying the spread of diseases or climate change.
All critical changes in networked systems have one thing in common: a tipping point where the system makes a transition from a base state to a new state. This may be a smooth shift, where the system can easily return to the base state. Or it can be a sharp, difficult-to-reverse transition where the system state can change abruptly or "explosively." Transitions of this kind also occur in climate change, for example with the melting of the polar ice caps. In many cases, the transitions result from the variation of a single parameter, such as the rise in concentrations of greenhouse gases behind climate change.
















Comment: Website The Cosmic Tusk comments that the discovery claim is still up for debate, but that much of the response from the scientific community has been far from scientific: See also: