Robust Control Optimization for Quantum Approximate Optimization Algorithm
arXiv:1911.00789
Abstract
Quantum variational algorithms have garnered significant interest recently, due to their feasibility of being implemented and tested on noisy intermediate scale quantum (NISQ) devices. We examine the robustness of the quantum approximate optimization algorithm (QAOA), which can be used to solve certain quantum control problems, state preparation problems, and combinatorial optimization problems. We demonstrate that the error of QAOA simulation can be significantly reduced by robust control optimization techniques, specifically, by sequential convex programming (SCP), to ensure error suppression in situations where the source of the error is known but not necessarily its magnitude. We show that robust optimization improves both the objective landscape of QAOA as well as overall circuit fidelity in the presence of coherent errors and errors in initial state preparation.
8 pages, 4 figures
References in corpus (6)
- A Quantum Approximate Optimization Algorithm
- Robust control of quantum gates via sequential convex programming
- Quantum approximate optimization is computationally universal
- Robust Quantum Control in Games: an Adversarial Learning Approach
- Optimal control of superconducting gmon qubits using Pontryagin's minimum principle: preparing a maximally entangled state with singular bang-bang protocols
- Optimal control of two qubits via a single cavity drive in circuit quantum electrodynamics
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