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Parameterized quantum circuits are widely studied approaches for tackling optimization problems.
Learning to learn with quantum neural networks via classical neural networks
Guillaume Verdon, Michael Broughton, Jarrod R. McClean, Kevin J. Sung, Ryan Babbush, Zhang Jiang, Hartmut Neven, and Masoud Mohseni · 1907
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Improving Variational Quantum Optimization using CVaR
Panagiotis Kl Barkoutsos, Giacomo Nannicini, Anton Robert, Ivano Tavernelli, and Stefan Woerner · 1907
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Multistart Methods for Quantum Approximate optimization
Ruslan Shaydulin, Ilya Safro, and Jeffrey Larson · 1971
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Practical methods of optimization
R. (Roger) Fletcher · 1987
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Quantum search heuristics
Tad Hogg · 2000
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Quantum optimization
Tad Hogg and Dmitriy Portnov · 2000
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Avoiding local minima in variational quantum eigensolvers with the natural gradient optimizer
David Wierichs, Christian Gogolin, and Michael Kastoryano · 2004
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Classical symmetries and the Quantum Approximate Optimization Algorithm
Ruslan Shaydulin, Stuart Hadfield, Tad Hogg, and Ilya Safro · 2012
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A Quantum Approximate Optimization Algorithm
Edward Farhi, Jeffrey Goldstone, and Sam Gutmann · 2014
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Beating the random assignment on constraint satisfaction problems of bounded degree
Boaz Barak, Ankur Moitra, Ryan O’Donnell, Prasad Raghavendra, Oded Regev, David Steurer, Luca Trevisan, Aravindan Vijayaraghavan, David Witmer, and John Wright · 2015
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Barren plateaus in quantum neural network training landscapes
Jarrod R. McClean, Sergio Boixo, Vadim N. Smelyanskiy, Ryan Babbush, 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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Fernando G. S. L. Brandao, Michael Broughton, Edward Farhi, Sam Gutmann, and Hartmut Neven · 2018
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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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From the Quantum Approximate Optimization Algorithm to a Quantum Alternating Operator Ansatz
Stuart Hadfield, Zhihui Wang, Bryan O’Gorman, Eleanor G. Rieffel, Davide Venturelli, and Rupak Biswas · 2019
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Classical and quantum bounded depth approximation algorithms
Matthew Hastings · 2019
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Learning to Optimize Variational Quantum Circuits to Solve Combinatorial Problems
Sami Khairy, Ruslan Shaydulin, Lukasz Cincio, Yuri Alexeev, and Prasanna Balaprakash · 2020
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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
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Accelerating quantum approximate optimization algorithm using machine learning
Mahabubul Alam, Abdullah Ash-Saki, and Swaroop Ghosh · 2020
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Training the quantum approximate optimization algorithm without access to a quantum processing unit
Michael Streif and Martin Leib · 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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Optimal Protocols in Quantum Annealing and Quantum Approximate Optimization Algorithm Problems
Lucas T. Brady, Christopher L. Baldwin, Aniruddha Bapat, Yaroslav Kharkov, and Alexey V. Gorshkov · 2021
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Quantum annealing initialization of the quantum approximate optimization algorithm
Stefan H. Sack and Maksym Serbyn · 2021
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Counterdiabaticity and the quantum approximate optimization algorithm
Jonathan Wurtz and Peter J. Love · 2021
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Parameters Fixing Strategy for Quantum Approximate Optimization Algorithm
Xinwei Lee, Yoshiyuki Saito, Dongsheng Cai, and Nobuyoshi Asai · 2021
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Transferability of optimal QAOA parameters between random graphs
Alexey Galda, Xiaoyuan Liu, Danylo Lykov, Yuri Alexeev, and Ilya Safro · 2021
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Using models to improve optimizers for variational quantum algorithms
Kevin J Sung, Jiahao Yao, Matthew P Harrigan, Nicholas C Rubin, Zhang Jiang, Lin Lin, Ryan Babbush, and Jarrod R McClean · 2020
Cited alongside, same era.
SciPy 1.0: fundamental algorithms for scientific computing in Python
Pauli Virtanen, Ralf Gommers, Travis E. Oliphant, Matt Haberland, Tyler Reddy, David Cournapeau, Evgeni Burovski, Pearu Peterson, Warren Weckesser, Jonathan Bright, Stéfan J. van der Walt, Matthew Brett, Joshua Wilson, K. Jarrod Millman, Nikolay Mayorov, Andrew R. J. Nelson, Eric Jones, Robert Kern, Eric Larson, C. J. Carey, İlhan Polat, Yu Feng, Eric W. Moore, Jake VanderPlas, Denis Laxalde, Josef Perktold, Robert Cimrman, Ian Henriksen, E. A. Quintero, Charles R. Harris, Anne M. Archibald, Antônio H. Ribeiro, Fabian Pedregosa, and Paul van Mulbregt · 2020
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Variational quantum algorithms
M. Cerezo, Andrew Arrasmith, Ryan Babbush, Simon C. Benjamin, Suguru Endo, Keisuke Fujii, Jarrod R. McClean, Kosuke Mitarai, Xiao Yuan, Lukasz Cincio, and Patrick J. Coles · 2021
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Noise-induced barren plateaus in variational quantum algorithms
Samson Wang, Enrico Fontana, M. Cerezo, Kunal Sharma, Akira Sone, Lukasz Cincio, and Patrick J. Coles · 2021
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Empirical performance bounds for quantum approximate optimization
Phillip C. Lotshaw, Travis S. Humble, Rebekah Herrman, James Ostrowski, and George Siopsis · 2021
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QAOAKit: A Toolkit for Reproducible Study, Application, and Verification of the QAOA
Ruslan Shaydulin, Kunal Marwaha, Jonathan Wurtz, and Phillip C. Lotshaw · 2021
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Optimizing quantum heuristics with meta-learning
Max Wilson, Rachel Stromswold, Filip Wudarski, Stuart Hadfield, Norm M. Tubman, and Eleanor G. Rieffel · 2021
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Behavior of analog quantum algorithms
Lucas T Brady, Lucas Kocia, Przemyslaw Bienias, Aniruddha Bapat, Yaroslav Kharkov, and Alexey V Gorshkov · 2021
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Local classical MAX-CUT algorithm outperforms p=2 QAOA on high-girth regular graphs
Kunal Marwaha · 2021
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Analytical framework for quantum alternating operator ansätze
Stuart Hadfield, Tad Hogg, and Eleanor G Rieffel · 2021
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HybridQ: A Hybrid Simulator for Quantum Circuits
Salvatore Mandrà, Jeffrey Marshall, Eleanor G. Rieffel, and Rupak Biswas · 2021
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Diagnosing barren plateaus with tools from quantum optimal control
Martin Larocca, Piotr Czarnik, Kunal Sharma, Gopikrishnan Muraleedharan, Patrick J. Coles, and M. Cerezo · 2022
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Limitations of local quantum algorithms on random Max-k-XOR and beyond
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