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The Quantum Approximate Optimization Algorithm (QAOA) is a general purpose quantum algorithm designed for combinatorial optimization.
Obstacles to variational quantum optimization from symmetry protection
Sergey Bravyi, Alexander Kliesch, Robert Koenig, and Eugene Tang · 1910
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Edward Farhi, Jeffrey Goldstone, Sam Gutmann, and Leo Zhou · 1910
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The overlap gap property and approximate message passing algorithms for p p -spin models
David Gamarnik and Aukosh Jagannath · 1911
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A sequence of approximated solutions to the SK model for spin glasses
Giorgio Parisi · 1980
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Algorithms for quantum computation: discrete logarithms and factoring
Peter W. Shor · 1994
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Optimization of mean-field spin glasses
Ahmed El Alaoui, Andrea Montanari, and Mark Sellke · 2001
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The thermodynamic limit in mean field spin glass models
Francesco Guerra and Fabio L. Toninelli · 2002
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The Quantum Approximate Optimization Algorithm Needs to See the Whole Graph: A Typical Case
Edward Farhi, David Gamarnik, and Sam Gutmann · 2004
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The Quantum Approximate Optimization Algorithm Needs to See the Whole Graph: Worst Case Examples
Edward Farhi, David Gamarnik, and Sam Gutmann · 2005
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The Parisi formula
Michel Talagrand · 2006
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The Sherrington-Kirkpatrick model
Dmitry Panchenko · 2013
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A Quantum Approximate Optimization Algorithm
Edward Farhi, Jeffrey Goldstone, and Sam Gutmann · 2014
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Limits of local algorithms over sparse random graphs
David Gamarnik and Madhu Sudan · 2014
Cited alongside, same era.
Quantum Supremacy through the Quantum Approximate Optimization Algorithm
Edward Farhi and Aram W Harrow · 2016
Cited alongside, same era.
Extremal cuts of sparse random graphs
Amir Dembo, Andrea Montanari, and Subhabrata Sen · 2017
Cited alongside, same era.
Quantum approximate optimization is computationally universal
Seth Lloyd · 2018
Cited alongside, same era.
On the K K -sat model with large number of clauses
Dmitry Panchenko · 2018
Cited alongside, same era.
Sami Boulebnane and Ashley Montanaro · 2021
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Instance Independence of Single Layer Quantum Approximate Optimization Algorithm on Mixed-Spin Models at Infinite Size
Jahan Claes and Wim van Dam · 2021
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Limitations of Local Quantum Algorithms on Random Max-k-XOR and Beyond
Chi-Ning Chou, Peter J Love, Juspreet Singh Sandhu, and Jonathan Shi · 2021
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The overlap gap property: A topological barrier to optimizing over random structures
David Gamarnik · 2021
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Circuit lower bounds for the p-spin optimization problem
David Gamarnik, Aukosh Jagannath, and Alexander S Wein · 2021
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Optimization on sparse random hypergraphs and spin glasses
Subhabrata Sen · 2018
Cited alongside, same era.
Suboptimality of local algorithms for a class of max-cut problems
Wei-Kuo Chen, David Gamarnik, Dmitry Panchenko, and Mustazee Rahman · 2019
Cited alongside, same era.
Optimization of the Sherrington-Kirkpatrick Hamiltonian
A. Montanari · 2019
Cited alongside, same era.
Low-degree hardness of random optimization problems
David Gamarnik, Aukosh Jagannath, and Alexander S Wein · 2020
Cited alongside, same era.
Leo Zhou, Sheng-Tao Wang, Soonwon Choi, Hannes Pichler, and Mikhail D. Lukin · 2020
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.
Ahmed El Alaoui, Andrea Montanari, and Mark Sellke · 2021
Cited alongside, same era.
Later among the works it cites.
Tight lipschitz hardness for optimizing mean field spin glasses
Brice Huang and Mark Sellke · 2021
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Hamiltonian singular value transformation and inverse block encoding
Seth Lloyd, Bobak T Kiani, David RM Arvidsson-Shukur, Samuel Bosch, Giacomo De Palma, William M Kaminsky, Zi-Wen Liu, and Milad Marvian · 2021
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MaxCut quantum approximate optimization algorithm performance guarantees for p > 1 p>1
Jonathan Wurtz and Peter Love · 2021
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Joao Basso, Edward Farhi, Kunal Marwaha, Benjamin Villalonga, and Leo Zhou · 2022
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Solving boolean satisfiability problems with the quantum approximate optimization algorithm
Sami Boulebnane and Ashley Montanaro · 2022
Closest in time.
Quantum optimization of maximum independent set using rydberg atom arrays
Sepehr Ebadi, Alexander Keesling, Madelyn Cain, Tout T. Wang, Harry Levine, Dolev Bluvstein, Giulia Semeghini, Ahmed Omran, Jinguo Liu, Rhine Samajdar, Xiu-Zhe Luo, Beatrice Nash, Xun Gao, Boaz Barak, Edward Farhi, Subir Sachdev, Nathan Gemelke, Leo Zhou, Soonwon Choi, Hannes Pichler, Shengtao Wang, Markus Greiner, Vladan Vuletic, and Mikhail D. Lukin · 2022
Closest in time.