Cycled reverse annealing on D-Wave devices shows schedule-dependent basin occupation with hardware autocorrelations bracketed between classical and quantum equilibrium references, and a pre-registered linear landscape predictor fails on held-out instances.
How "Quantum" is the D-Wave Machine?
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abstract
Recently there has been intense interest in claims about the performance of the D-Wave machine. In this paper, we outline a simple classical model, and show that it achieves excellent correlation with published input-output behavior of the D-Wave One machine on 108 qubits. While raising questions about "how quantum" the D-Wave machine is, the new model also provides additional algorithmic insights into the nature of the native computational problem solved by the D-Wave machine.
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Quantum annealing is described as a heuristic for discrete optimization and sampling that also serves as a platform for studying non-equilibrium many-body quantum dynamics with programmable spin systems.
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Schedule-dependent basin occupation in a programmable quantum annealer
Cycled reverse annealing on D-Wave devices shows schedule-dependent basin occupation with hardware autocorrelations bracketed between classical and quantum equilibrium references, and a pre-registered linear landscape predictor fails on held-out instances.
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Quantum Annealing: Optimisation, Sampling, and Many-Body Dynamics
Quantum annealing is described as a heuristic for discrete optimization and sampling that also serves as a platform for studying non-equilibrium many-body quantum dynamics with programmable spin systems.