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Generation and Coherent Control of Pulsed Quantum Frequency Combs
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Coherent controlization using superconducting qubits.

Nicolai Friis1, Alexey A Melnikov1,2, Gerhard Kirchmair2,3

  • 1Institute for Theoretical Physics, University of Innsbruck, Technikerstraße 21a, A-6020 Innsbruck, Austria.

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|December 16, 2015
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Summary
This summary is machine-generated.

We propose a new scheme for coherent controlization of superconducting qubits, crucial for quantum computing algorithms and quantum learning agents. This method enables flexible control of quantum operations, adaptable to dynamic computational needs.

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Area of Science:

  • Quantum Computing
  • Quantum Information Science
  • Superconducting Qubits

Background:

  • Coherent controlization enables flexible implementation of quantum algorithms.
  • Dynamic subroutines and frequent modifications are key in quantum learning agents.
  • Superconducting qubits are a leading platform for quantum computation.

Purpose of the Study:

  • To propose a scheme for coherent controlization of any number of superconducting qubits coupled to a microwave resonator.
  • To provide explicit constructions for two- and three-qubit systems.
  • To demonstrate the feasibility of the proposed scheme under realistic conditions.

Main Methods:

  • Utilizing a microwave resonator to couple multiple superconducting qubits.
  • Developing an explicit construction for coherent controlization in two- and three-qubit systems.
  • Simulating the scheme's performance considering loss, dephasing, and cavity self-Kerr effects.

Main Results:

  • A feasible scheme for coherent controlization of multiple superconducting qubits is presented.
  • Explicit constructions for two- and three-qubit coherent controlization are derived.
  • The scheme's robustness against noise and unwanted cavity effects is demonstrated.

Conclusions:

  • The proposed scheme offers a flexible and feasible approach to coherent controlization for superconducting quantum systems.
  • This work is highly relevant for advancing quantum learning agents and other dynamic quantum algorithms.
  • The demonstrated feasibility paves the way for practical implementations in quantum computation.