Differential Equation Models for Sharp Threshold Dynamics

Abstract

We develop an extension to differential equation models of dynamical systems to allow us to analyze probabilistic threshold dynamics that fundamentally change system behavior. We apply our novel modeling approach to two cases of interest: a model of cyber infection, where a detection event drastically changes dynamics, and the Lanchester model of armed conflict, where the loss of a key capability drastically changes dynamics. We derive and demonstrate a stepby- step, repeatable method for applying our novel modeling approach to an arbitrary system, and we compare the resulting differential equations to simulations of the system’s random progression. Our work leads to a simple and easily implemented method for analyzing probabilistic threshold dynamics using differential equations.