Entropy (Jul 2023)

Proposal for Trapped-Ion Quantum Memristor

  • Sergey Stremoukhov,
  • Pavel Forsh,
  • Ksenia Khabarova,
  • Nikolay Kolachevsky

DOI
https://doi.org/10.3390/e25081134
Journal volume & issue
Vol. 25, no. 8
p. 1134

Abstract

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A quantum memristor combines the memristive dynamics with the quantum behavior of the system. We analyze the idea of a quantum memristor based on ultracold ions trapped in a Paul trap. Corresponding input and output memristor signals are the ion electronic levels populations. We show that under certain conditions the output/input dependence is a hysteresis curve similar to classical memristive devices. This behavior becomes possible due to the partial decoherence provided by the feedback loop, which action depends on previous state of the system (memory). The feedback loop also introduces nonlinearity in the system. Ion-based quantum memristor possesses several advantages comparing to other platforms—photonic and superconducting circuits—due to the presence of a large number of electronic levels with different lifetimes as well as strong Coulomb coupling between ions in the trap. The implementation of the proposed ion-based quantum memristor will be a significant contribution to the novel direction of “quantum neural networks”.

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