Preprint Article Version 1 This version is not peer-reviewed

Numerical Modelling of Vortex-Based Superconducting Memory Cells: Dynamics and Geometrical Optimization

Version 1 : Received: 27 August 2024 / Approved: 27 August 2024 / Online: 28 August 2024 (10:47:52 CEST)

How to cite: Skog, A.; Hovhannisyan, R. A.; Krasnov, V. M. Numerical Modelling of Vortex-Based Superconducting Memory Cells: Dynamics and Geometrical Optimization. Preprints 2024, 2024082020. https://doi.org/10.20944/preprints202408.2020.v1 Skog, A.; Hovhannisyan, R. A.; Krasnov, V. M. Numerical Modelling of Vortex-Based Superconducting Memory Cells: Dynamics and Geometrical Optimization. Preprints 2024, 2024082020. https://doi.org/10.20944/preprints202408.2020.v1

Abstract

The lack of dense random-access memory is one of the main obstacles to the development of digital superconducting computers. It has been suggested that AVRAM cells, based on the storage of a single Abrikosov vortex — the smallest quantized object in superconductors — can enable drastic miniaturization to the nanometer scale. In this work, we present numerical modeling of such cells using time-dependent Ginzburg-Landau equations. The cell represents a fluxonic quantum dot containing a small superconducting island, an asymmetric notch for vortex entrance, a guiding track, and a vortex trap. We determine the optimal geometrical parameters for operation at zero magnetic field and the conditions for controllable vortex manipulation by short current pulses. We report ultra-fast vortex motion with velocities more than an order of magnitude faster than those expected for macroscopic superconductors. This phenomenon is attributed to strong interactions with the edges of a mesoscopic island, combined with the nonlinear reduction of flux-flow viscosity due to nonequilibrium effects in the track. Our results show that such cells can be scaled down to sizes comparable to the London penetration depth, ∼100 nm, and can enable ultrafast switching on the picosecond scale with ultra-low energy per operation, ∼10−19 J.

Keywords

Josephson effect; superconductivity; digital electronics; nano-devices

Subject

Physical Sciences, Applied Physics

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