Ultralow power artificial synapses using nanotextured magnetic Josephson junctions

Abstract

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.

Fig. 1. Spin-dependent superconducting transport.

(A) Schematic of the JJ synapse in the magnetically disordered state (left) and the magnetically ordered state (right). (B) Data (blue circles) and fit to the resistively shunted junction (RSJ) model (red line) of the voltage-current characteristic taken at 4 K on a 10-μm-diameter JJ synapse in the disordered state. The data are well fit with an RSJ shown in red. Lower inset: Simulated voltage spike train above I_c; the average of the spike train results in the measured quasi-static voltage measured. Upper inset: Schematic showing the magnetically disordered state of the junction for this measurement. (C) Data (blue circles) and fit to the RSJ model (red line) of the voltage versus current characteristic taken at 4 K on the same 10-μm-diameter JJ synapse in the ordered state. Inset: Schematic showing the magnetically ordered state of the junction for this measurement. (D) Fraunhofer diffraction of the same JJ synapse in varying magnetic ordered states. The most ordered state is in red, disorder is increased for black and magenta, and most disordered data are in blue. Black data are offset by 0.3 mA, magenta data are offset by 0.6 mA, and blue data are offset by 0.9 mA. Data are shown as squares with fits to the Airy function shown as lines.

Fig. 2. Device operation and scaling.

(A) Critical current measured in a zero field after the application of electrical ordering pulses (ordering pulses were applied in a 20-mT magnetic field); the line serves as a visual guide. (B) Electric pulse energy required to magnetically order the JJ synapse in a 20-mT applied magnetic field (red squares) and SFQ pulse energy (blue circles) versus JJ synapse cross-sectional area.

Fig. 3. JJ synapse SPICE simulation.

(A) Circuit diagram used in the simulation, where I_c of JJ₁ = JJ₂ = JJ₃ = 200 μA, L₁ = L₃ = 3 pH (picohenry), L₂ = 5 pH, and R₁ = 100 milliohm. (B) Peak current through the coupling inductor L₂ versus I_c of the MJJ. I_c values within the blue box are those measured in a single MJJ. (C) Circuit operation with low magnetic order I_c = 100 μA (low synaptic weight) showing the phase modulation of the presynaptic (input) JJ (blue), the JJ synapse (black), the postsynaptic (output) JJ (red), and the output voltage (red right axis). (D) Circuit operation with high magnetic order I_c = 50 μA (high synaptic weight) showing the phase modulation of the presynaptic (input) JJ (blue), the JJ synapse (black), the postsynaptic (output) JJ (red), and the output voltage (red left axis).

Fig. 4. SPICE simulation of stochasticity.

(A) Measured critical current of a 10-μm JJ synapse in the partially ordered magnetic state as a function of temperature (black circles); lines serve as visual guides. Simulated stochasticity of a 100-nm JJ synapse as a function of temperature (blue squares). (B) Block diagram of the circuit model. (C) Voltage at output (black) and magnetic order (blue) as a function of time simulated at 2 K. (D) Voltage at output (black) and magnetic order (blue) as a function of time simulated at 3 K.

Fig. 5. Magnetic nanocluster properties.

(A) Magnetic moment versus temperature under zero field–cooled (ZFC) (black) and field-cooled (red) conditions. The peak in the zero field–cooled curve gives a measure of the energy required to reorient the magnetic clusters. (B) Magnetic moment versus applied magnetic field at 70 K; data are in blue circles, and Langevin fit to the data are shown as a red line. The Langevin fit gives an estimated magnetic cluster density and moment of 2 × 10⁴ Mn clusters/μm² and 2000 μ_B, respectively.