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Related Experiment Video

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Gradient Echo Quantum Memory in Warm Atomic Vapor
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Defects in Quantum Computers.

Bartłomiej Gardas1,2,3, Jacek Dziarmaga4, Wojciech H Zurek1

  • 1Theoretical Division, LANL, Los Alamos, New Mexico, 87545, USA.

Scientific Reports
|March 16, 2018
PubMed
Summary
This summary is machine-generated.

We developed a simple test for quantum annealing hardware using the quantum Ising chain. This test measures imperfections by counting topological defects, assessing how well the hardware performs adiabatic quantum computation.

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Area of Science:

  • Quantum Computing
  • Condensed Matter Physics

Background:

  • Interest is shifting from general-purpose quantum computers to quantum annealing.
  • A broadly applicable and easy-to-implement test is needed to assess quantum annealing hardware.
  • Existing methods may not be universally applicable or straightforward.

Purpose of the Study:

  • To propose and implement a test for evaluating the performance of quantum annealing hardware.
  • To quantify the 'quantumness' or 'adiabaticity' of a specific quantum computing hardware.
  • To provide a benchmark for assessing the quality of adiabatic quantum computation.

Main Methods:

  • Utilized an exactly solvable many-body system: the quantum Ising chain in a transverse field.
  • Implemented the test on the D-Wave quantum annealing machine.
  • Simulated an adiabatic quench process and analyzed the resulting spin configurations.

Main Results:

  • An ideal adiabatic quench should result in an ordered, broken-symmetry ground state with all spins aligned.
  • Imperfections (decoherence, noise, Hamiltonian flaws, non-adiabaticity) lead to topological defects (kinks).
  • The number of topological defects directly quantifies the deviation from the ideal ground state.

Conclusions:

  • The proposed test effectively quantifies the imperfections in quantum annealing processes.
  • Topological defect counts serve as a metric for assessing the quality of adiabatic quantum computation on hardware.
  • This method offers a practical approach to benchmark and improve quantum annealing systems.