Toward Learning in Neuromorphic Circuits Based on Quantum Phase Slip Junctions

We explore the use of superconducting quantum phase slip junctions (QPSJs), an electromagnetic dual to Josephson Junctions (JJs), in neuromorphic circuits. These small circuits could serve as the building blocks of neuromorphic circuits for machine learning applications because they exhibit desirable properties such as inherent ultra-low energy per operation, high speed, dense integration, negligible loss, and natural spiking responses. In addition, they have a relatively straight-forward micro/nano fabrication, which shows promise for implementation of an enormous number of lossless interconnections that are required to realize complex neuromorphic systems. We simulate QPSJ-only, as well as hybrid QPSJ + JJ circuits for application in neuromorphic circuits including artificial synapses and neurons, as well as fan-in and fan-out circuits. We also design and simulate learning circuits, where a simplified spike timing dependent plasticity rule is realized to provide potential learning mechanisms. We also take an alternative approach, which shows potential to overcome some of the expected challenges of QPSJ-based neuromorphic circuits, via QPSJ-based charge islands coupled together to generate non-linear charge dynamics that result in a large number of programmable weights or non-volatile memory states. Notably, we show that these weights are a function of the timing and frequency of the input spiking signals and can be programmed using a small number of DC voltage bias signals, therefore exhibiting spike-timing and rate dependent plasticity, which are mechanisms to realize learning in neuromorphic circuits.

High dynamic resistance elements based on a Josephson junction array

A chain of superconductor–insulator–superconductor junctions based on Al–AlO x –Al nanostructures and fabricated using conventional lift-off lithography techniques was measured at ultra-low temperatures. At zero magnetic field, the low current bias dynamic resistance can reach values of ≈1011 Ω. It was demonstrated that the system can provide a decent quality current biasing circuit, enabling the observation of Coulomb blockade and Bloch oscillations in ultra-narrow Ti nanowires associated with the quantum phase-slip effect.

High dynamic resistance elements based on Josephson junction array

Chain of superconductor-insulator-superconductor junctions based on Al-AlO x -Al... lift-off fabricated nanostructures was measured at ultra-low temperatures. At zero magnetic field the low current bias dynamic resistance can reach values ~1011 W. The system has been proved to provide a decent quality current biasing circuit enabling observation of Coulomb blockade and Bloch oscillations in ultra-narrow Ti nanowires associated with quantum phase slip effect.

Duality between coherent quantum phase-slip and the Josephson junction in nanowires by dual Hamiltonian method

A method was devised to construct a generalized dual field theory with a quantum field theory named the dual Hamiltonian (DH) method. As a simple example using this method, we examined the duality between coherent quantum phase-slip and Josephson junction (JJ) in single junction systems and nanowires. This method was proved to be reliable within the Villain approximation.