Defining the Tipping Point Based on Conditionally Convergent Series: Explaining the Indeterminacy

Abstract

Tipping Point refers to the moment when an adaption or infection sustains itself in network without further external inputs. Until now, studies have mainly focused on the occurrence of the Tipping Point and what it leads to rather than what precedes it. This paper explores the situation leading to the Tipping Point during a process of diffusion in networks. The core of the debate is to manifest that the process can be introduced as an example of conditionally convergent series and that determining the tipping points' occurrence is conditional to the arrangement of the series based on Reimann Rearrangement Theorem. Accordingly, the occurrence of curve does not follow a general formulation. That is called indeterminacy since that the predictions about tipping points for any diffusion over the network may include a variety of right answers, although such indeterminacy neither means there is no tipping point nor many.