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Quantum approximate optimization is one of the promising candidates for useful quantum computation, particularly in the context of finding approximate solutions to Quadratic Unconstrained Binary Optimization (QUBO) problems.
Solvable model of a spin-glass
David Sherrington and Scott Kirkpatrick · 1975
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The max-cut problem and quadratic 0–1 optimization; polyhedral aspects, relaxations and bounds
Endre Boros and Peter L. Hammer · 1991
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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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Heuristic algorithms for the unconstrained binary quadratic programming problem, 1998
John E Beasley · 1998
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Simulated annealing for discrete optimization with estimation
Talal M. Alkhamis, Mohamed A. Ahmed, and Vu Kim Tuan · 1999
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Rank-two relaxation heuristics for max-cut and other binary quadratic programs
Samuel Burer, Renato D. C. Monteiro, and Yin Zhang · 2002
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Multiscale approach for the network compression-friendly ordering
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Algebraic distance on graphs
Jie Chen and Ilya Safro · 2011
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The university of florida sparse matrix collection
Timothy A. Davis and Yifan Hu · 2011
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Fast response to infection spread and cyber attacks on large-scale networks
Sven Leyffer and Ilya Safro · 2013
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Experimental signature of programmable quantum annealing
Sergio Boixo, Tameem Albash, Federico M Spedalieri, Nicholas Chancellor, and Daniel A Lidar · 2013
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Making a science of model search: Hyperparameter optimization in hundreds of dimensions for vision architectures
James Bergstra, Daniel Yamins, and David Cox · 2013
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A quantum approximate optimization algorithm
Edward Farhi, Jeffrey Goldstone, and Sam Gutmann · 2014
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A hybrid quantum-classical approach to solving scheduling problems
Tony Tran, Minh Do, Eleanor Rieffel, Jeremy Frank, Zhihui Wang, Bryan O’Gorman, Davide Venturelli, and J Beck · 2016
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What works best when? a systematic evaluation of heuristics for max-cut and QUBO
Iain Dunning, Swati Gupta, and John Silberholz · 2018
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Design and execution of quantum circuits using tens of superconducting qubits and thousands of gates for dense Ising optimization problems, 2023
Filip B. Maciejewski, Stuart Hadfield, Benjamin Hall, Mark Hodson, Maxime Dupont, Bram Evert, James Sud, M. Sohaib Alam, Zhihui Wang, Stephen Jeffrey, Bhuvanesh Sundar, P. Aaron Lott, Shon Grabbe, Eleanor G. Rieffel, Matthew J. Reagor, and Davide Venturelli · 2023
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Quantum optimization: Potential, challenges, and the path forward, 2023
Amira Abbas, Andris Ambainis, Brandon Augustino, Andreas Bärtschi, Harry Buhrman, Carleton Coffrin, Giorgio Cortiana, Vedran Dunjko, Daniel J. Egger, Bruce G. Elmegreen, Nicola Franco, Filippo Fratini, Bryce Fuller, Julien Gacon, Constantin Gonciulea, Sander Gribling, Swati Gupta, Stuart Hadfield, Raoul Heese, Gerhard Kircher, Thomas Kleinert, Thorsten Koch, Georgios Korpas, Steve Lenk, Jakub Marecek, Vanio Markov, Guglielmo Mazzola, Stefano Mensa, Naeimeh Mohseni, Giacomo Nannicini, Corey O’Meara, Elena Peña Tapia, Sebastian Pokutta, Manuel Proissl, Patrick Rebentrost, Emre Sahin, Benjamin C. B. Symons, Sabine Tornow, Victor Valls, Stefan Woerner, Mira L. Wolf-Bauwens, Jon Yard, Sheir Yarkoni, Dirk Zechiel, Sergiy Zhuk, and Christa Zoufal · 2023
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Quantum critical dynamics in a 5,000-qubit programmable spin glass
Andrew D. King, Jack Raymond, Trevor Lanting, Richard Harris, Alex Zucca, Fabio Altomare, Andrew J. Berkley, Kelly Boothby, Sara Ejtemaee, Colin Enderud, Emile Hoskinson, Shuiyuan Huang, Eric Ladizinsky, Allison J. R. MacDonald, Gaelen Marsden, Reza Molavi, Travis Oh, Gabriel Poulin-Lamarre, Mauricio Reis, Chris Rich, Yuki Sato, Nicholas Tsai, Mark Volkmann, Jed D. Whittaker, Jason Yao, Anders W. Sandvik, and Mohammad H. Amin · 2023
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Optimizing the spin reversal transform on the d-wave 2000q
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Optuna: A next-generation hyperparameter optimization framework
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Qubit-efficient encoding schemes for binary optimisation problems
Benjamin Tan, Marc-Antoine Lemonde, Supanut Thanasilp, Jirawat Tangpanitanon, and Dimitris G Angelakis · 2021
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Multilevel combinatorial optimization across quantum architectures
Hayato Ushijima-Mwesigwa, Ruslan Shaydulin, Christian FA Negre, Susan M Mniszewski, Yuri Alexeev, and Ilya Safro · 2021
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Modeling and mitigation of cross-talk effects in readout noise with applications to the quantum approximate optimization algorithm
Filip B Maciejewski, Flavio Baccari, Zoltán Zimborás, and Michał Oszmaniec · 2021
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Quantum optimization of maximum independent set using rydberg atom arrays
S. Ebadi, A. Keesling, M. Cain, T. T. Wang, H. Levine, D. Bluvstein, G. Semeghini, A. Omran, J.-G. Liu, R. Samajdar, X.-Z. Luo, B. Nash, X. Gao, B. Barak, E. Farhi, S. Sachdev, N. Gemelke, L. Zhou, S. Choi, H. Pichler, S.-T. Wang, M. Greiner, V. Vuletić, and M. D. Lukin · 2022
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Quantum optimization with arbitrary connectivity using rydberg atom arrays
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Quantum computing in logistics and supply chain management-an overview
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