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International Journal of Engineering & Technology

Theory of a quantum artificial neuron based on superconducting devices

Haruna Katayama, Toshiyuki Fujii, Noriyuki Hatakenaka

Published Aug 24, 2018• 0 citations
Publisher

Abstract

An artificial neuron using superconducting devices, so-called rf SQUID, working at the quantum-mechanical domain is studied. It is shown that quantum rf SQUID regarded as flux qubit can act as an artificial neuron with sigmoid function generated by coherent quantum-mechanical transitions between wells in double well potential representing rf SQUID.

DOI
10.14419/ijet.v7i3.29.18546

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Conventional rf SQUIDs (superconducting quantum interference devices) consist of a superconducting loop interrupted by one weak link, and when read out via a tank circuit they produce output signals in the order of a few tens of microvolts. When the single weak link is replaced by a dc SQUID (a superconducting loop with two junctions) a so-called double quantization loop SQUID is formed. In this paper it is shown theoretically, and supported experimentally with thin-film devices of three different designs, that the general behaviour can be explained by a simplified picture of the fixed critical current of the single junction of the rf SQUID being replaced by an effective critical current of a dc SQUID loop that is varied by the applied magnetic flux (i.e., we have a rf SQUID with a variable β parameter). A more detailed analysis of the experimental data and the theory of this novel device reveals its interesting nonlinear character and shows the deviations from this simple picture. It is demonstrated experimentally that output signals in the order of ≥1 mV can be obtained with a suitable read-out mode for the tank circuit, a clear advantage when compared to conventional rf SQUIDs. With respect to dc SQUIDs, the coupling to integrated planar input coils will be unproblematic since no microwave resonances should occur in the structures.
We report on the development and test of an integrated system composed of a flux qubit and a rapid single-flux quantum (RSFQ) circuit that allows qubit manipulation. The goal is to demonstrate the feasibility of control electronics integrated on the same chip as the qubit, in view of the application in quantum computation with superconducting devices. RSFQ logic relies on the storage and transmission of magnetic flux quanta and can be profitably used with superconducting qubits because of the speed, scalability, compatibility with the qubit fabrication process and low temperature environment. While standard RSFQ circuitry is well assessed, the application to quantum computing requires a complete rescaling of parameter values, in order to preserve the qubit coherence and reduce the power dissipation. In the system presented in this paper, the qubit role is played by a superconducting loop interrupted by a small dc SQUID, usually called a double SQUID, which behaves as a tunable rf-SQUID. Its energy potential has the shape of a double well, with the barrier between the wells controlled by magnetic flux applied to the inner dc SQUID. Here for the first time we report measurements at a base temperature of 370 mK in which flux control pulses with desired characteristics were supplied by a RSFQ circuit fabricated using non-standard parameters in the same chip as the qubit.
The concept of creating an element base for superconducting quantum neural networks based on only a single flux qubit is presented. The behavior of the activation function is analyzed for different variants of the “quantum neuron” implementation (based on three-contact, two-contact, and five-contact interferometers), and the conditions at which this activation function is close to a sigmoid curve are determined. The prospects of using energy-efficient upgrades to the rapid single-flux-quantum logic to control the transfer and activation functions when operating a quantum neural network based on the proposed elements are discussed.