Synchronization dynamics on the picosecond timescale in coupled Josephson junction neurons

Abstract

Conventional digital computation is rapidly approaching physical limits for speed and energy dissipation. Here we fabricate and test a simple neuromorphic circuit that models neuronal somas, axons and synapses with superconducting Josephson junctions. The circuit models two mutually coupled excitatory neurons. 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.

13 pages, 8 figures

References in corpus (3)

• Neuromorphic electronic circuits for building autonomous cognitive systems
• Josephson junction simulation of neurons
• Sign- and magnitude-tunable coupler for superconducting flux qubits

Cited by in corpus (19)

• Memristive control of mutual SHNO synchronization for neuromorphic computing
• Applications and Techniques for Fast Machine Learning in Science
• Fan-out and Fan-in properties of superconducting neuromorphic circuits
• Optoelectronic Intelligence
• Easy-plane spin Hall nano-oscillators as spiking neurons for neuromorphic computing
• Chaos and relaxation oscillations in spin-torque windmill neurons
• A new family of bioSFQ logic/memory cells
• Low-temperature emergent neuromorphic networks with correlated oxide devices
• From phase to amplitude oscillators
• Integrated-photonic characterization of single-photon detectors for use in neuromorphic synapses
• An active dendritic tree can mitigate fan-in limitations in superconducting neurons
• Single Flux Quantum Based Ultrahigh Speed Spiking Neuromorphic Processor Architecture
• Chaotic Antiferromagnetic Nano-Oscillator driven by Spin-Torque
• Deep Neuromorphic Networks with Superconducting Single Flux Quanta
• Self-training superconducting neuromorphic circuits using reinforcement learning rules
• Does Cosmological Evolution Select for Technology?
• The birefringent spin-laser as a system of coupled harmonic oscillators
• Digital-analog concept for superconducting perceptron-like neural networks
• Chaos synchronization between the Josephson junctions governed by the central junction under the effect of parameter mismatches and noise