UCLA

The emergent dynamical behaviors of biological neuronal networks and other natural, complex systems point towards new computing paradigms which can overcome limitations of digital computers. This work catalogues the development and characterization of an electronic circuit purpose built to exhibit emergent behaviors intended for use in neuromorphic computation. These circuits, atomic switch networks (ASNs), are fabricated through a self-assembly process that yields a highly interconnected network of silver nanowires with embedded inorganic synapses known as atomic switches. When stimulated with external bias voltage, ASNs are shown to possess the synaptic and memory properties of individual atomic switches, as well as network-specific behavior consisting of distributed, system wide switching events. These emergent behaviors exhibit striking similarity to those observed in many natural systems, including biological neural networks. Experiment and numerical simulations have provided proof of principle that ASNs are complex systems whose emergent behaviors may be used in implementations of neuromorphic computing paradigms such as reservoir computing. Furthermore, they demonstrate the utility of ASNs as a uniquely scalable physical platform useful for exploring complexity, neuroscience, and engineering.