High-Speed and Low-Power Superconducting Neuromorphic Circuits Based on Quantum Phase-Slip Junctions

Abstract

The quantum phase-slip junctions (QPSJs) resulting from quantum fluctuation of superconducting order parameter in 1-D superconducting nanowires are explained as exact duals to Josephson junctions (JJs). An overdamped QPSJ can generate a current pulse to emulate a spiking event in biological neurons. We have demonstrated spiking neuron circuits and synaptic circuits using QPSJs in our previous work through simulations in WRspice. The neuron circuit can fire a current pulse as soon as the capacitor voltage is above a threshold, which is similar to an integrate-and-fire neuron (IFN). The synaptic circuit, either based on magnetic JJs and QPSJs or only using QPSJs, functions as an adjustable weighted connection between neurons. To overcome existing problems, such as fan-out limitations, and further explore the possible applications of QPSJs in superconducting neuromorphic computing, we propose new neuromorphic circuits based on QPSJs and JJs in this paper. The neuron, synapse and fan-out circuits operate through the transfer of quantized charge or fluxons, providing circuit operations that emulate brain functions. Since the fabrication of reproducible QPSJ elements remains at a preliminary stage, the demonstration of our circuits design has been primarily done in WRspice simulation with a QPSJ SPICE model.