Memristive nanowires exhibit small-world connectivity

Abstract

Small-world networks provide an excellent balance of efficiency and robustness that is not available with other network topologies. These characteristics are exhibited in the Memristive Nanowire Neural Network (MN³), a novel neuromorphic hardware architecture. This architecture is composed of an electrode array connected by stochastically deposited core-shell nanowires. We simulate the stochastic behavior of the nanowires by making various assumptions on their paths. First, we assume that the nanowires follow straight paths. Next, we assume that they follow arc paths with varying radii. Last, we assume that they follow paths generated by pink noise. For each of the three methods, we present a method to find whether a nanowire passes over an electrode, allowing us to represent the architecture as a bipartite graph. We find that the small-worldness coefficient increases logarithmically and is consistently greater than one, which is indicative of a small-world network.

Keywords: Memristors; Nanowires; Network science; Neuromorphics; Small-world.