Dynamics of autonomous time-delay Boolean networks

The nascent field of network science aims to describe a complex system as a collection of nodes that interact via links. Examples include neuronal networks, disease spreading networks, the power grid network, etc. Much of the research has focused on analyzing existing data sets or on studying mathematical models, often by computer simulation. I will discuss our new approach for purposefully designing networks that allows us to investigate experimentally a wide range of network dynamics. From this approach, we have made discoveries in several areas, from the dynamics and control of a model of a small neuronal network, to the observation of extremely long transient behavior in a model of a gene regulatory network, to the generation of high speed random numbers. I will introduce the basic concept of networks, how we realize them experimentally, and touch on our recent efforts to develop reservoir computers using autonomous Boolean logic elements with time-delay feedback.