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The quantum approximate optimization algorithm (QAOA) is a variational method for noisy, intermediate-scale quantum computers to solve combinatorial optimization problems.
Numerical Recipes in Fortran 77: The Art of Scientific Computing
William H. Press, Brian P. Flannery, and Saul A. Teukolsky · 1993
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Improved approximation algorithms for maximum cut and satisfiability problems using semidefinite programming
Michel X. Goemans and David P. Williamson · 1995
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Couenne: A user’s manual
Pietro Belotti · 2009
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Branching and bounds tighteningtechniques for non-convex MINLP
Pietro Belotti, Jon Lee, Leo Liberti, Francois Margot, and Andreas Wächter · 2009
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A quantum approximate optimization algorithm
Edward Farhi, Jeffrey Goldstone, and Sam Gutmann · 2014
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Near-optimal quantum circuit for Grover’s unstructured search using a transverse field
Zhang Jiang, Eleanor G. Rieffel, and Zhihui Wang · 2017
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Quantum approximate optimization algorithm for MaxCut: A fermionic view
Zhihui Wang, Stuart Hadfield, Zhang Jiang, and Eleanor G Rieffel · 2018
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Quantum algorithms for scientific computing and approximate optimization
Stuart Hadfield · 2018
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Fernando G. S. L. Brandão, Michael Broughton, Edward Farhi, Sam Gutmann, and Hartmut Neven · 2018
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Performance of the quantum approximate optimization algorithm on the maximum cut problem
Gavin E Crooks · 2018
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Quantum supremacy using a programmable superconducting processor
Frank Arute, Kunal Arya, Ryan Babbush, Dave Bacon, Joseph C Bardin, Rami Barends, Rupak Biswas, Sergio Boixo, Fernando GSL Brandao, David A Buell, et al · 2019
Cited alongside, same era.
QAOA for Max-Cut requires hundreds of qubits for quantum speed-up
G G. Guerreschi and A. Y. Matsuura · 2019
Cited alongside, same era.
Evaluating quantum approximate optimization algorithm: A case study
R. Shaydulin and Y. Alexeev · 2019
Cited alongside, same era.
Quantum computational advantage using photons
Han-Sen Zhong, Hui Wang, Yu-Hao Deng, Ming-Cheng Chen, Li-Chao Peng, Yi-Han Luo, Jian Qin, Dian Wu, Xing Ding, Yi Hu, Peng Hu, Xiao-Yan Yang, Wei-Jun Zhang, Hao Li, Yuxuan Li, Xiao Jiang, Lin Gan, Guangwen Yang, Lixing You, Zhen Wang, Li Li, Nai-Le Liu, Chao-Yang Lu, and Jian-Wei Pan · 2020
Cited alongside, same era.
Quantum approximate optimization algorithm: Performance, mechanism, and implementation on near-term devices
Leo Zhou, Sheng-Tao Wang, Soonwon Choi, Hannes Pichler, and Mikhail D. Lukin · 2020
Cited alongside, same era.
Reachability deficits in quantum approximate optimization
V. Akshay, H. Philathong, M. E. S. Morales, and J. D. Biamonte · 2020
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What do QAOA energies reveal about graphs?
Mario Szegedy · 2020
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Quantum approximate optimization of the long-range Ising model with a trapped-ion quantum simulator
Guido Pagano, Aniruddha Bapat, Patrick Becker, Katherine S. Collins, Arinjoy De, Paul W. Hess, Harvey B. Kaplan, Antonis Kyprianidis, Wen Lin Tan, Christopher Baldwin, Lucas T. Brady, Abhinav Deshpande, Fangli Liu, Stephen Jordan, Alexey V. Gorshkov, and Christopher Monroe · 2020
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Linghua Zhu, Ho Lun Tang, Gearge S. Barron, Nicholas J. Mayhall, Edwin Barnes, and Sophia E. Economou · 2020
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Grover mixers for QAOA: Shifting complexity from mixer design to state preparation
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Classical variational simulation of the quantum approximate optimization algorithm
Matija Medvidović and Giuseppe Carleo · 2020
Cited alongside, same era.
Bounds on MAXCUT QAOA performance for p > 1 p>1
Jonathan Wurtz and Peter Love · 2020
Cited alongside, same era.
Ruslan Shaydulin, Stuart Hadfield, Tad Hogg, and Ilya Safro · 2020
Cited alongside, same era.
Lower bounds on circuit depth of the quantum approximate optimization algorithm
James Ostrowski, Rebekah Herrman, Travis S. Humble, and George Siopsis · 2020
Cited alongside, same era.
X Y XY -mixers: analytical and numerical results for the quantum alternating operator ansatz
Zhihui Wang, Nicholas C Rubin, Jason M Dominy, and Eleanor G. Rieffel
Cited in the paper.
QAOA dataset
Phillip C. Lotshaw and Travis S. Humble
Cited in the paper.
Andreas Bärtschi and Stephan Eidenbenz · 2020
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The quantum alternating operator ansatz on maximum k k -vertex cover
Jeremy Cook, Stephan Eidenbenz, and Andreas Bärtschi · 2020
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Quantum optimization with a novel Gibbs objective function and ansatz architecture search
Li Li, Minjie Fan, Marc Coram, Patrick Riley, and Stefan Leichenauer · 2020
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Bridging classical and quantum with SDP initialized warm-starts for QAOA
Reuben Tate, Majid Farhadi, Creston Herold, Greg Mohler, and Swati Gupta · 2020
Later among the works it cites.
Impact of graph structures for QAOA on MaxCut
Rebekah Herrman, Lorna Treffert, James Ostrowski, Phillip C. Lotshaw, Travis S. Humble, and George Siopsis · 2021
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