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Experimental Adiabatic Quantum Factorization under Ambient Conditions Based on a Solid-State Single Spin System.

Kebiao Xu1, Tianyu Xie1, Zhaokai Li1,2

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

Physical Review Letters
|April 15, 2017
PubMed
Summary

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This summary is machine-generated.

Researchers experimentally realized an adiabatic quantum algorithm using a solid spin system at room temperature. This robust quantum computing method successfully factored 35 into its prime factors, 5 and 7.

Area of Science:

  • Quantum Computing
  • Quantum Algorithms
  • Solid-State Physics

Background:

  • Adiabatic quantum computation is a universal and robust quantum computing method.
  • It involves evolving a quantum system from an initial Hamiltonian to a final one encoding the problem's solution.
  • This approach is a promising candidate for scalable quantum computation.

Purpose of the Study:

  • To experimentally realize an adiabatic quantum algorithm.
  • To demonstrate the feasibility of this approach on a single solid spin system under ambient conditions.

Main Methods:

  • Experimental realization of all key elements of adiabatic quantum computation.
  • Initial state preparation.
  • Adiabatic evolution simulated by optimal control.

Related Experiment Videos

  • Final state read-out.
  • Utilizing a single solid spin system at ambient conditions.

    • Main Results:

    • Successful experimental implementation of an adiabatic quantum algorithm.
    • Demonstration of initial state preparation, adiabatic evolution, and final state read-out.
    • Found the ground state of the problem Hamiltonian S_{z}I_{z}.
    • Mapped the problem to the factorization of 35 into its prime factors 5 and 7.

    Conclusions:

    • The experimental realization validates adiabatic quantum computation on a solid spin system.
    • This work demonstrates a practical approach to implementing quantum algorithms under ambient conditions.
    • The method shows potential for scalable quantum computation and solving complex problems like factorization.