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December 19, 2012

Experimental signature of programmable quantum annealing last for up to 20 milliseconds

Arxiv - Experimental signature of programmable quantum annealing (12 pages) This work shows that Dwave Systems adiabatic quantum computing system is leveraging quantum effects for up to 20 milliseconds. Different experiments are needed to calculate the speedup relative to optimal classical systems.

Quantum annealing is a general strategy for solving difficult optimization problems with the aid of quantum adiabatic evolution. Both analytical and numerical evidence suggests that under idealized, closed system conditions, quantum annealing can outperform classical thermalization-based algorithms such as simulated annealing. Do engineered quantum annealing devices effectively perform classical thermalization when coupled to a decohering thermal environment? To address this we establish, using superconducting flux qubits with programmable spin-spin couplings, an experimental signature which is consistent with quantum annealing, and at the same time inconsistent with classical thermalization, in spite of a decoherence timescale which is orders of magnitude shorter than the adiabatic evolution time. This suggests that programmable quantum devices, scalable with current superconducting technology, implement quantum annealing with a surprising robustness against noise and imperfections.



We thus arrive at our main conclusion: signatures of QA, as opposed to classical thermalization, persist for timescales that are much longer than the single-qubit
decoherence time (from 5µs to 20ms vs tens of ns) in programmable devices available with present-day superconducting technology. Our experimental results are also consistent with numerical methods that compute quantum statistics, such as Path Integral Monte Carlo. Our study focuses on demonstrating a non-classical signature in experimental QA. Different methods are required to address the question of experimental computational speedups of open system QA relative to optimal classical
algorithms.

SOURCE - Arxiv


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