Results 71 to 80 of about 548 (174)
Physical Review X, 2020 The quantum approximate optimization algorithm (QAOA) is a hybrid quantum-classical variational algorithm designed to tackle combinatorial optimization problems.
Leo Zhou +4 more
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Quantum Approximation for Wireless Scheduling
Applied Sciences, 2020 This paper proposes an application algorithm based on a quantum approximate optimization algorithm (QAOA) for wireless scheduling problems. QAOA is one of the promising hybrid quantum-classical algorithms to solve combinatorial optimization problems and ...
Jaeho Choi, Seunghyeok Oh, Joongheon Kim
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FUTURES &FORESIGHT SCIENCE, Volume 7, Issue 3, December 2025.ABSTRACT Quantum technologies, driven by principles of quantum mechanics like superposition and entanglement, have shown transformative potential in drug discovery, medical diagnosis, precision medicine, and other therapeutic interventions. However, the research on emerging quantum technologies at early to late stages of development for healthcare ...
Oshin Sharma +4 more
wiley +1 more source
Nanophotonics, Volume 14, Issue 23, Page 3761-3793, 02 November 2025.Abstract Photonic device development (PDD) has achieved remarkable success in designing and implementing new devices for controlling light across various wavelengths, scales, and applications, including telecommunications, imaging, sensing, and quantum information processing.
Yuheng Chen +18 more
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An improved QAOA algorithm based on multi-angle and RY-assisted structure
Tongxin xuebaoThe standard quantum approximate optimization algorithm (QAOA) has a limited expressive power in shallow circuits, whereas naively increasing the number of layers leads to greater quantum circuit depth and higher noise sensitivity.
Tian-Yu Ye, Peng-Hui Ma, Zhi-Gang Gan
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Universal resources for quantum approximate optimization algorithm and quantum annealing
Physical Review ResearchThe quantum approximate optimization algorithm (QAOA) is a variational ansatz that resembles the Trotterized dynamics of a quantum annealing (QA) protocol.
Pablo Díez-Valle +3 more
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Shallow-depth QAOA on sparse, high-diameter MaxCut instances faces a locality bottleneck: at depth \(p\), local observables can depend only on a bounded neighborhood of the circuit interaction graph. We propose a transport-augmented QAOA that keeps the MaxCut cost Hamiltonian unchanged but enriches the mixer with optimized, unweighted shortcut ...
Kumar, Mithilesh, Tahir, Yusuf
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Prog-QAOA: Framework for resource-efficient quantum optimization through classical programs [PDF]
QuantumCurrent state-of-the-art quantum optimization algorithms require representing the original problem as a binary optimization problem, which is then converted into an equivalent cost Hamiltonian suitable for the quantum device.
Bence Bakó +3 more
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Scaling whole-chip QAOA for higher-order ising spin glass models on heavy-hex graphs
npj Quantum InformationWe show that the quantum approximate optimization algorithm (QAOA) for higher-order, random coefficient, heavy-hex compatible spin glass Ising models has strong parameter concentration across problem sizes from 16 up to 127 qubits for p = 1 up to p = 5 ...
Elijah Pelofske +4 more
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Improved QAOA based on multi-angle and RY-assisted structure
Tongxin xuebaoTo address the limited expressive capability of the standard quantum approximate optimization algorithm (QAOA) in shallow circuits and the increased noise sensitivity caused by deeper quantum circuits, an improved QAOA, termed MA-RY-QAOA, was proposed by
Ye Tianyu, Ma Penghui, Gan Zhigang
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