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Bulletin of the American Physical Society

Assessing claims of quantum annealing: Does D-Wave have a quantum computer?

John A. Smolin, Graeme Smith

Published Mar 4, 2014• 0 citations
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Progress on exploring practical applications of quantum annealing and D-Wave One

Sergio Boixo, Federico M. Spedalieri

Bulletin of the American Physical Society•Feb 29, 2012•0 citations

Assessing the quantumness of the annealing dynamics via Leggett Garg’s inequalities: a weak measurement approach

Vittorio Vitale, G. De Filippis, ANTONIO DE CANDIA +3 more

Adiabatic quantum computation (AQC) is a promising counterpart of universal quantum computation, based on the key concept of quantum annealing (QA). QA is claimed to be at the basis of commercial quantum computers and benefits from the fact that the detrimental role of decoherence and dephasing seems to have poor impact on the annealing towards the ground state. While many papers show interesting optimization results with a sizable number of qubits, a clear evidence of a full quantum coherent behavior during the whole annealing procedure is still lacking. In this paper we show that quantum non-demolition (weak) measurements of Leggett Garg inequalities can be used to efficiently assess the quantumness of the QA procedure. Numerical simulations based on a weak coupling Lindblad approach are compared with classical Langevin simulations to support our statements.

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Thermal Quantum Annealing on the D-Wave device

Anurag Mishra, Walter Vinci, Tameem Albash +2 more

Bulletin of the American Physical Society•Mar 4, 2014•0 citations

Single-Qubit Fidelity Assessment of Quantum Annealing Hardware

Jon Nelson, Marc Vuffray, Andrey Y. Lokhov +1 more

As a wide variety of quantum computing platforms become available, methods for assessing and comparing the performance of these devices are of increasing interest and importance. Inspired by the success of single-qubit error rate computations for tracking the progress of gate-based quantum computers, this work proposes a quantum annealing single-qubit assessment (QASA) protocol for quantifying the performance of individual qubits in quantum annealing computers. The proposed protocol scales to large quantum annealers with thousands of qubits and provides unique insights into the distribution of qubit properties within a particular hardware device. The efficacy of the QASA protocol is demonstrated by analyzing the properties of a D-Wave 2000Q system, revealing unanticipated correlations in the qubit performance of that device. A study repeating the QASA protocol at different annealing times highlights how the method can be utilized to understand the impact of annealing parameters on qubit performance. Overall, the proposed QASA protocol provides a useful tool for assessing the performance of current and emerging quantum annealing devices.

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Simulations of Thermal Quantum Annealing on the D-Wave Device

Tameem Albash, Walter Vinci, Anurag Mishra +2 more

Bulletin of the American Physical Society•Mar 4, 2014•0 citations

Comparing Quantum Annealing and BF-DCQO

Pau Farré, Erika Ordog, Kevin T. Chern +1 more

Recent work [1] has claimed that a gate-model quantum-classical hybrid algorithm called bias-field digitized counterdiabatic quantum optimization (BF-DCQO) [2] outperforms D-Wave's annealing quantum computers in optimization tasks. We find the opposite to be true, and demonstrate that D-Wave's quantum annealers find solutions of far greater quality than claimed in Ref. [1], while using far less computation time. We also present evidence that suggests the quantum component of the hybrid approach makes minimal contributions to solution quality.

arXiv:2509.14358•Sep 17, 2025•0 citations
Adiabatic quantum computation (AQC) is a promising counterpart of universal quantum computation, based on the key concept of quantum annealing (QA). QA is claimed to be at the basis of commercial quantum computers and benefits from the fact that the detrimental role of decoherence and dephasing seems to have poor impact on the annealing towards the ground state. While many papers show interesting optimization results with a sizable number of qubits, a clear evidence of a full quantum coherent behavior during the whole annealing procedure is still lacking. In this paper we show that quantum non-demolition (weak) measurements of Leggett Garg inequalities can be used to efficiently assess the quantumness of the QA procedure. Numerical simulations based on a weak coupling Lindblad approach are compared with classical Langevin simulations to support our statements.
As a wide variety of quantum computing platforms become available, methods for assessing and comparing the performance of these devices are of increasing interest and importance. Inspired by the success of single-qubit error rate computations for tracking the progress of gate-based quantum computers, this work proposes a quantum annealing single-qubit assessment (QASA) protocol for quantifying the performance of individual qubits in quantum annealing computers. The proposed protocol scales to large quantum annealers with thousands of qubits and provides unique insights into the distribution of qubit properties within a particular hardware device. The efficacy of the QASA protocol is demonstrated by analyzing the properties of a D-Wave 2000Q system, revealing unanticipated correlations in the qubit performance of that device. A study repeating the QASA protocol at different annealing times highlights how the method can be utilized to understand the impact of annealing parameters on qubit performance. Overall, the proposed QASA protocol provides a useful tool for assessing the performance of current and emerging quantum annealing devices.
Recent work [1] has claimed that a gate-model quantum-classical hybrid algorithm called bias-field digitized counterdiabatic quantum optimization (BF-DCQO) [2] outperforms D-Wave's annealing quantum computers in optimization tasks. We find the opposite to be true, and demonstrate that D-Wave's quantum annealers find solutions of far greater quality than claimed in Ref. [1], while using far less computation time. We also present evidence that suggests the quantum component of the hybrid approach makes minimal contributions to solution quality.