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An improved differential evolution algorithm for learning high-fidelity quantum controls.

Xiaodong Yang1, Jun Li2, Xinhua Peng3

  • 1CAS Key Laboratory of Microscale Magnetic Resonance and Department of Modern Physics, University of Science and Technology of China, Hefei 230026, China.

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|January 20, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces daDE, an improved evolutionary algorithm for designing quantum control pulses. It enhances efficiency and robustness in quantum computation tasks, even with system uncertainties.

Keywords:
Control pulses searchingDifferential evolutionPulse imperfectionsQuantum states and gates preparationRandom measurement errors

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Area of Science:

  • Quantum Information Science
  • Quantum Control
  • Computational Physics

Background:

  • Designing quantum control pulses is crucial for quantum computation.
  • Gradient-based methods are common but struggle with system uncertainties and calibration issues.
  • Gradient-free evolutionary algorithms offer an alternative but are often inefficient.

Purpose of the Study:

  • To develop a more efficient and robust gradient-free algorithm for designing quantum control pulses.
  • To address the limitations of traditional gradient-based and evolutionary methods in quantum control.

Main Methods:

  • Introduced an improved differential evolution algorithm named daDE.
  • Designed an efficient mutation rule utilizing information from current and previous individuals.
  • Numerically benchmarked daDE for quantum state and gate preparation on a Nuclear Magnetic Resonance (NMR) system.

Main Results:

  • daDE demonstrated superior convergence speed compared to conventional differential evolution algorithms.
  • The algorithm showed significant robustness against uncertainties like pulse imperfections and measurement errors.
  • Successful pulse optimization for quantum state and gate preparation was achieved.

Conclusions:

  • The daDE algorithm offers an efficient and robust solution for designing quantum control pulses.
  • It overcomes key limitations of existing methods, particularly in the presence of system uncertainties.
  • This advancement is vital for practical quantum computation and control.