Think Super: Artificial Neurons made from Superconductors - by Ken Segall
Ken Segall Department of Physics & Astronomy, Colgate University
Host: Britton Plourde | Contact: Tyler Engstrom, email@example.com
Our research focuses on the design, fabrication and testing of integrated circuits which can simulate neuron spiking dynamics on very fast timescales. These circuits are based on a low-temperature, superconducting electronics technology (Josephson junctions) that has already been successful in creating ultra-sensitive magnetometers, high-performance radiation detectors, high-speed digital processors, and the primary voltage standard in the U.S. The short spiking times in these artificial neurons combined with analog scaling properties give this approach a potentially unprecedented ability to investigate long term dynamics of large networks. In addition, these artificial neurons dissipate almost no power, making them a candidate for a low-power, neuromorphic computing technology.
We have performed the first experiments on two superconducting neurons which are mutually coupled with artificial axons and synapses. In some regions of parameter space the neurons are desynchronized. In others, the Josephson neurons synchronize in one of two states, in-phase or anti-phase. An experimental alteration of the delay and strength of the connecting synapses can toggle the system back and forth in a phase-flip bifurcation. Firing synchronization states are calculated >70,000 times faster than conventional digital approaches. With their speed and low energy dissipation (10-17 Joules/spike), this set of proof-of-concept experiments establishes Josephson junction neurons as a viable approach for improvements in neuronal computation as well as applications in neuromorphic computing.
A Lithographic Superconducting Circuit Interconnected Neurons