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We introduce an optimisation method for variational quantum algorithms and experimentally demonstrate a 100-fold improvement in efficiency compared to naive implementations.
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Error mitigation extends the computational reach of a noisy quantum processor
Kandala, A. et al · 2019
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An adaptive variational algorithm for exact molecular simulations on a quantum computer
Grimsley, H. R., Economou, S. E., Barnes, E. & Mayhall, N. J · 2019
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Nakamura, I., Kanemura, A., Nakaso, T., Yamamoto, R. & Fukuhara, T · 2019
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Zhu, D. et al · 2019
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Qiskit: An open-source framework for quantum computing (2019)
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Demonstration of quantum volume 64 on a superconducting quantum computing system
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Bayesian optimal control of greenberger-horne-zeilinger states in rydberg lattices
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Optimal quantum control with poor statistics
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Using models to improve optimizers for variational quantum algorithms
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McClean, J. R. et al · 2020
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Quantum approximate optimization of non-planar graph problems on a planar superconducting processor
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Effect of data encoding on the expressive power of variational quantum-machine-learning models
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Mitigating measurement errors in multiqubit experiments
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