Search Results - "Quantum approximate optimization algorithm"

Modified recursive QAOA for exact MAX-CUT solutions on bipartite graphs: closing the gap beyond QAOA limit by Bae, Eunok, Kwon, Hyukjoon, Vijendran, V, Lee, Soojoon

“…Quantum approximate optimization algorithm (QAOA) is a quantum–classical hybrid algorithm proposed with the goal of approximately solving combinatorial…”
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A review on Quantum Approximate Optimization Algorithm and its variants by Blekos, Kostas, Brand, Dean, Ceschini, Andrea, Chou, Chiao-Hui, Li, Rui-Hao, Pandya, Komal, Summer, Alessandro

“…The Quantum Approximate Optimization Algorithm (QAOA) is a highly promising variational quantum algorithm that aims to solve combinatorial optimization…”
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Genetic algorithms as classical optimizer for the Quantum Approximate Optimization Algorithm by Acampora, Giovanni, Chiatto, Angela, Vitiello, Autilia

“…Optimization is one of the research areas where quantum computing could bring significant benefits. In this scenario, a hybrid quantum–classical variational…”
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A study of the performance of classical minimizers in the Quantum Approximate Optimization Algorithm by Fernández-Pendás, Mario, Combarro, Elías F., Vallecorsa, Sofia, Ranilla, José, Rúa, Ignacio F.

“…The Quantum Approximate Optimization Algorithm (QAOA) was proposed as a way of finding good, approximate solutions to hard combinatorial optimization problems…”
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Novel Resolution of Unit Commitment Problems Through Quantum Surrogate Lagrangian Relaxation by Feng, Fei, Zhang, Peng, Bragin, Mikhail A., Zhou, Yifan

“…Unit commitment (UC) problems faced by Independent System Operators on a daily basis are becoming increasingly complex due to the recent push for renewables…”
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Exploiting Symmetry Reduces the Cost of Training QAOA by Shaydulin, Ruslan, Wild, Stefan M.

“…A promising approach to the practical application of the quantum approximate optimization algorithm (QAOA) is finding QAOA parameters classically in simulation…”
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Applying the quantum approximate optimization algorithm to the minimum vertex cover problem by Zhang, Y.J., Mu, X.D., Liu, X.W., Wang, X.Y., Zhang, X., Li, K., Wu, T.Y., Zhao, D., Dong, C.

“…The minimum vertex cover problem belongs to a NP- complete problem, which is difficult to obtain the near-optimal solution in the polynomial time range using…”
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Rapidly trainable and shallow-compiled quantum approximate optimization algorithm for maximum likelihood detection by Liu, Yuxiang, Qian, Yinuo, Wang, Lu, Zhang, Zaichen, Yu, Xutao

“…In multiple-input and multiple-output (MIMO) systems, the maximum likelihood (ML) detection problem is NP-hard and becomes increasingly complex with more…”
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Theoretical approximation ratios for Warm-Started QAOA on 3-regular max-cut instances at depth p=1 by Tate, Reuben, Eidenbenz, Stephan

“…We generalize Farhi et al.’s 0.6924-approximation result technique of the Max-Cut Quantum Approximate Optimization Algorithm (QAOA) on 3-regular graphs to…”
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Application of quantum approximate optimization algorithm to job shop scheduling problem by Kurowski, Krzysztof, Pecyna, Tomasz, Slysz, Mateusz, Różycki, Rafał, Waligóra, Grzegorz, Wȩglarz, Jan

“…•Demonstrate how to efficiently apply Quantum Approximate Optimization Algorithm (QAOA) to Job Shop Scheduling Problem (JSSP).•Investigation of the behaviour…”
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Classical symmetries and the Quantum Approximate Optimization Algorithm by Shaydulin, Ruslan, Hadfield, Stuart, Hogg, Tad, Safro, Ilya

“…We study the relationship between the Quantum Approximate Optimization Algorithm (QAOA) and the underlying symmetries of the objective function to be…”
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Max-flow min-cut theorem in quantum computing by Singh, Nongmeikapam Brajabidhu, Roy, Arnab, Saha, Anish Kumar

“…The max-flow min-cut theorem in graph theory states that the maximum flow of a network is equal to the minimum cut of edges of the flow network. Max-flow and…”
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Large-Scale Quantum Approximate Optimization via Divide-and-Conquer by Li, Junde, Alam, Mahabubul, Ghosh, Swaroop

“…Quantum approximate optimization algorithm (QAOA) is a promising hybrid quantum-classical algorithm for solving combinatorial optimization problems. However,…”
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Improved Performance of Multi-Angle Quantum Approximate Optimization Algorithm (ma-QAOA) Compared to QAOA On Simulation and Experimental Hardware Platforms by Srivastava, Vandit, P, Rohith, Singhal, Sanyam, Bhowmik, Debanjan

“…Multi-angle quantum approximate optimization algorithm (ma-QAOA) has been proposed as an alternative to regular QAOA for solving optimization problems using…”
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Quantum Approximate Optimization Algorithm applied to multi-objective routing for large scale 6G networks by Bouchmal, Oumayma, Cimoli, Bruno, Stabile, Ripalta, Vegas Olmos, Juan Jose, Tafur Monroy, Idelfonso

“…A multi-objective optimization problem involves optimizing two or more conflicting objectives simultaneously. This type of problem arises in many scientific…”
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Improving the performance of quantum approximate optimization for preparing non-trivial quantum states without translational symmetry by Sun, Zheng-Hang, Wang, Yong-Yi, Cui, Jian, Fan, Heng

“…The variational preparation of complex quantum states using the quantum approximate optimization algorithm (QAOA) is of fundamental interest, and becomes a…”
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Improvement of Quantum Approximate Optimization Algorithm for Max–Cut Problems by Villalba-Diez, Javier, González-Marcos, Ana, Ordieres-Meré, Joaquín B.

“…The objective of this short letter is to study the optimal partitioning of value stream networks into two classes so that the number of connections between…”
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Hamiltonian switching control of noisy bipartite qubit systems by Yang, Zhibo, Kosut, Robert L, Birgitta Whaley, K

“…We develop a Hamiltonian switching ansatz for bipartite control that is inspired by the quantum approximate optimization algorithm, to mitigate environmental…”
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A quantum approximate optimization method for finding Hadamard matrices by Suksmono, Andriyan Bayu

“…Finding a Hadamard matrix of a specific order using a quantum computer can lead to a demonstration of practical quantum advantage. Earlier efforts using a…”
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Quantum computing and quantum-inspired techniques for feature subset selection: a review by Mandal, Ashis Kumar, Chakraborty, Basabi

“…Feature subset selection is essential for identifying relevant and non-redundant features, which enhances classification accuracy and simplifies machine…”
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