The statistical dynamics of programmed self-assembly

Abstract

We describe how a graph grammar program for robotic self-assembly, together with measurements of kinetic rate data yield a Markov process model of the dynamics of programmed self-assembly. We demonstrate and validate the method by applying it to a physical testbed consisting of a number of "programmable parts", which are able to control their local interactions according to their on-board programs. We describe a technique for obtaining kinetic rate constants from simulation and a comparison of the behavior predicted by the Markov model with the behavior predicted by a high-fidelity simulation of the system