Results 11 to 20 of about 548 (174)
Elementary proof of QAOA convergence
New Journal of PhysicsThe quantum alternating operator ansatz (QAOA) and its predecessor, the quantum approximate optimization algorithm, are one of the most widely used quantum algorithms for solving combinatorial optimization problems.
Lennart Binkowski +3 more
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Study on Quantum Approximation Optimization Algorithm in Airport Cargo Transportation Problem
Journal of Advanced TransportationThe vehicle routing problem (VRP) is a core NP-hard combinatorial optimization problem in logistics and supply chain management. Quantum computing, particularly the Quantum Approximate Optimization Algorithm (QAOA), is being explored as a promising ...
Xudong Zhao +3 more
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2022 IEEE 19th International Conference on Software Architecture Companion (ICSA-C), 2022 The Quantum Approximate Optimization Algorithm (QAOA) has been one of the leading candidates for near-term quantum advantage in gate-model quantum computers. From its inception, this algorithm has sparked the desire for comparison between gate-model and annealing platforms.
Colin Campbell, Edward Dahl
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Feature Selection for Classification with QAOA
2022 IEEE International Conference on Quantum Computing and Engineering (QCE), 2022 Feature selection is of great importance in Machine Learning, where it can be used to reduce the dimensionality of classification, ranking and prediction problems. The removal of redundant and noisy features can improve both the accuracy and scalability of the trained models.
Turati G. +2 more
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Scaling of the quantum approximate optimization algorithm on superconducting qubit based hardware [PDF]
Quantum, 2022 Quantum computers may provide good solutions to combinatorial optimization problems by leveraging the Quantum Approximate Optimization Algorithm (QAOA). The QAOA is often presented as an algorithm for noisy hardware.
Johannes Weidenfeller +6 more
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The Quantum Approximate Optimization Algorithm and the Sherrington-Kirkpatrick Model at Infinite Size [PDF]
Quantum, 2022 The Quantum Approximate Optimization Algorithm (QAOA) is a general-purpose algorithm for combinatorial optimization problems whose performance can only improve with the number of layers $p$.
Edward Farhi +3 more
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Bayesian Optimization for QAOA
IEEE Transactions on Quantum Engineering, 2023 The Quantum Approximate Optimization Algorithm (QAOA) adopts a hybrid quantum-classical approach to find approximate solutions to variational optimization problems. In fact, it relies on a classical subroutine to optimize the parameters of a quantum circuit. In this work we present a Bayesian optimization procedure to fulfil this optimization task, and
Simone Tibaldi +3 more
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Reachability Deficits in Quantum Approximate Optimization of Graph Problems [PDF]
Quantum, 2021 The quantum approximate optimization algorithm (QAOA) has become a cornerstone of contemporary quantum applications development. Here we show that the $density$ of problem constraints versus problem variables acts as a performance indicator.
V. Akshay +3 more
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Graph neural network initialisation of quantum approximate optimisation [PDF]
Quantum, 2022 Approximate combinatorial optimisation has emerged as one of the most promising application areas for quantum computers, particularly those in the near term.
Nishant Jain +3 more
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Solution of SAT problems with the adaptive-bias quantum approximate optimization algorithm
Physical Review Research, 2023 The quantum approximate optimization algorithm (QAOA) is a promising method for solving certain classical combinatorial optimization problems on near-term quantum devices. When employing the QAOA to 3-SAT and Max-3-SAT problems, the quantum cost exhibits
Yunlong Yu +4 more
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