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The quantum approximate optimization algorithm (QAOA) is a prospective near-term quantum algorithm due to its modest circuit depth and promising benchmarks.
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E. Farhi, J. Goldstone, S. Gutmann, and M. Sipser, Quantum Computation by Adiabatic Evolution, arXiv e-prints , quant-ph/0001106 (2000), arXiv:quant-ph/0001106 [quant-ph]
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E. Farhi, J. Goldstone, S. Gutmann, J. Lapan, A. Lundgren, and D. Preda, A Quantum Adiabatic Evolution Algorithm Applied to Random Instances of an NP-Complete Problem, Science 292
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F. Arute et al. , Hartree-Fock on a superconducting qubit quantum computer, Science 369
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Z.-C. Yang, A. Rahmani, A. Shabani, H. Neven, and C. Chamon, Optimizing variational quantum algorithms using Pontryagin’s minimum principle, Phys. Rev. X 7
2017
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D. W. Berry, G. Ahokas, R. Cleve, and B. C. Sanders, Efficient Quantum Algorithms for Simulating Sparse Hamiltonians, Communications in Mathematical Physics 270
2007
Cited alongside, same era.
D. Aharonov, W. van Dam, J. Kempe, Z. Landau, S. Lloyd, and O. Regev, Adiabatic Quantum Computation Is Equivalent to Standard Quantum Computation, SIAM Review 50
2008
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A. Hagberg, P. Swart, and D. S Chult, Exploring network structure, dynamics, and function using NetworkX , Tech. Rep. (Los Alamos National Lab.(LANL), Los Alamos, NM (United States), 2008)
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2009
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2010
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2010
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2011
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2018
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T. Albash and D. A. Lidar, Adiabatic quantum computation, Rev. Mod. Phys. 90
2018
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G. G. Guerreschi and A. Y. Matsuura, QAOA for Max-Cut requires hundreds of qubits for quantum speed-up, Scientific Reports 9
2019
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R. Shaydulin, I. Safro, and J. Larson, Multistart methods for quantum approximate optimization, in 2019 IEEE High Performance Extreme Computing Conference (HPEC) (2019) pp. 1–8
2019
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M. Heyl, P. Hauke, and P. Zoller, Quantum localization bounds Trotter errors in digital quantum simulation, Science Advances 5
2019
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D. Guéry-Odelin, A. Ruschhaupt, A. Kiely, E. Torrontegui, S. Martínez-Garaot, and J. G. Muga, Shortcuts to adiabaticity: Concepts, methods, and applications, Rev. Mod. Phys. 91
2019
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P. W. Claeys, M. Pandey, D. Sels, and A. Polkovnikov, Floquet-engineering counterdiabatic protocols in quantum many-body systems, Phys. Rev. Lett. 123
2019
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L. Zhou, S.-T. Wang, S. Choi, H. Pichler, and M. D. Lukin, Quantum approximate optimization algorithm: Performance, mechanism, and implementation on near-term devices, Phys. Rev. X 10
2020
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D. Liang, L. Li, and S. Leichenauer, Investigating quantum approximate optimization algorithms under bang-bang protocols, Phys. Rev. Research 2
2020
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P. Virtanen, R. Gommers, T. E. Oliphant, M. Haberland, T. Reddy, D. Cournapeau, E. Burovski, P. Peterson, W. Weckesser, J. Bright, S. J. van der Walt, M. Brett, J. Wilson, K. J. Millman, N. Mayorov, A. R. J. Nelson, E. Jones, R. Kern, E. Larson, C. J. Carey, İ. Polat, Y. Feng, E. W. Moore, J. VanderPlas, D. Laxalde, J. Perktold, R. Cimrman, I. Henriksen, E. A. Quintero, C. R. Harris, A. M. Archibald, A. H. Ribeiro, F. Pedregosa, P. van Mulbregt, and SciPy 1.0 Contributors, SciPy 1.0: Fundamental Algorithms for Scientific Computing in Python, Nature Methods 17
2020
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2021
Closest in time.
S. H. Sack, Trotterized quantum annealing initialization of the QAOA, https://github.com/shsack/TQA-init.-for-QAOA (2021)
2021
Closest in time.