Quantum Annealing for Industry Applications: Introduction and Review
arXiv:2112.07491 · doi:10.1088/1361-6633/ac8c54
Abstract
Quantum annealing is a heuristic quantum optimization algorithm that can be used to solve combinatorial optimization problems. In recent years, advances in quantum technologies have enabled the development of small- and intermediate-scale quantum processors that implement the quantum annealing algorithm for programmable use. Specifically, quantum annealing processors produced by D-Wave Systems have been studied and tested extensively in both research and industrial settings across different disciplines. In this paper we provide a literature review of the theoretical motivations for quantum annealing as a heuristic quantum optimization algorithm, the software and hardware that is required to use such quantum processors, and the state-of-the-art applications and proofs-of-concepts that have been demonstrated using them. The goal of our review is to provide a centralized and condensed source regarding applications of quantum annealing technology. We identify the advantages, limitations, and potential of quantum annealing for both researchers and practitioners from various fields.
major revision with extended noise section and discussion of alternative platforms
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- Application of QUBO solver using black-box optimization to structural design for resonance avoidance
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- Quantum approximate optimization algorithm for qudit systems
- Quantum Computing Techniques for Multi-Knapsack Problems
- Comparing Three Generations of D-Wave Quantum Annealers for Minor Embedded Combinatorial Optimization Problems
- Imaginary time evolution with quantum nondemolition measurements: multi-qubit interactions via measurement nonlinearities
- Noise Dynamics of Quantum Annealers: Estimating the Effective Noise Using Idle Qubits
- An Advantage Using Feature Selection with a Quantum Annealer
- Dynamic Asset Allocation with Expected Shortfall via Quantum Annealing
- Mapping State Transition Susceptibility in Quantum Annealing
- Calculating Nash Equilibrium on Quantum Annealers