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Quantum Memristors with Superconducting Circuits.

J Salmilehto1,2,3, F Deppe4,5,6, M Di Ventra7

  • 1Department of Physics, Yale University, New Haven, Connecticut 06520, USA.

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|February 15, 2017
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Summary
This summary is machine-generated.

Researchers designed a quantum memristor using superconducting circuits. This novel device exhibits memristive behavior through quasiparticle tunneling, paving the way for advanced quantum computing and electronics.

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Area of Science:

  • Quantum physics
  • Condensed matter physics
  • Electronics engineering

Background:

  • Memristors, resistive elements with memory, offer potential for advanced electronics and computing.
  • Quantum technologies are rapidly advancing, creating opportunities for novel quantum devices.
  • Superconducting circuits are a promising platform for implementing quantum phenomena.

Purpose of the Study:

  • To design and introduce a quantum memristor utilizing superconducting circuits.
  • To explore the memristive behavior arising from quasiparticle-induced tunneling.
  • To develop methods for quantifying memory retention in quantum memristive systems.

Main Methods:

  • Theoretical design of a quantum memristor based on superconducting circuits.
  • Analysis of quasiparticle-induced tunneling mechanisms for memristive behavior.
  • Simulation and theoretical validation using realistic device parameters.
  • Development of quantitative metrics for memory retention.

Main Results:

  • A quantum memristor design is proposed where memristive behavior originates from quasiparticle tunneling.
  • The hysteretic behavior characteristic of memristors can be observed under realistic experimental conditions.
  • The study introduces methods to effectively quantify the memory retention capabilities of the quantum memristor.

Conclusions:

  • The proposed quantum memristor design is feasible with current state-of-the-art measurement techniques.
  • This work lays the foundation for developing quantum memristive devices for future information processing and unconventional computing.
  • The developed quantification methods are crucial for evaluating and optimizing quantum memory retention.