Quantized Pulse Propagation in Josephson Junction Arrays.

We present time-domain electrical measurements and simulations of the quantized voltage pulses that are generated from series-connected Josephson junction (JJ) arrays. The transmission delay of the JJ array can lead to a broadening of the net output pulse, depending on the direction of the output pulse propagation relative to the input bias pulse. To demonstrate this, we compare time-domain measurements of output pulses from radio-frequency Josephson Arbitrary Waveform Synthesizer (RF-JAWS) circuits fabricated with two different output measurement configurations, so that the backward-propagating and forward-propagating pulses can be measured. Measurements were made on arrays with 1200 and 3600 JJs and show that the net backward-propagating output pulse is broadened by timing delays in the JJ array while the net forward-propagating output pulse is insensitive to delay effects and can theoretically be further scaled to longer JJ array lengths without significant output pulse broadening. These measurements match well with simulations and confirm the expectation that the net output pulses arise from the time-delayed superposition of individual JJ output pulses from the series array of JJs. The measurements and analysis shown here have important implications for the realization of RF-JAWS circuits to be used as quantum-based reference sources for communications metrology.

Ultralow power artificial synapses using nanotextured magnetic Josephson junctions.

Neuromorphic computing promises to markedly improve the efficiency of certain computational tasks, such as perception and decision-making. Although software and specialized hardware implementations of neural networks have made tremendous accomplishments, both implementations are still many orders of magnitude less energy efficient than the human brain. We demonstrate a new form of artificial synapse based on dynamically reconfigurable superconducting Josephson junctions with magnetic nanoclusters in the barrier. The spiking energy per pulse varies with the magnetic configuration, but in our demonstration devices, the spiking energy is always less than 1 aJ. This compares very favorably with the roughly 10 fJ per synaptic event in the human brain. Each artificial synapse is composed of a Si barrier containing Mn nanoclusters with superconducting Nb electrodes. The critical current of each synapse junction, which is analogous to the synaptic weight, can be tuned using input voltage spikes that change the spin alignment of Mn nanoclusters. We demonstrate synaptic weight training with electrical pulses as small as 3 aJ. Further, the Josephson plasma frequencies of the devices, which determine the dynamical time scales, all exceed 100 GHz. These new artificial synapses provide a significant step toward a neuromorphic platform that is faster, more energy-efficient, and thus can attain far greater complexity than has been demonstrated with other technologies.