Results 51 to 60 of about 2,321 (167)
New Journal of Physics, 2023 The variational preparation of complex quantum states using the quantum approximate optimization algorithm (QAOA) is of fundamental interest, and becomes a promising application of quantum computers.
Zheng-Hang Sun +3 more
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Engineering Reports, Volume 8, Issue 2, February 2026.Quantum computing techniques such as Quantum Annealing and Quadratic Unconstrained Binary Optimization are effectively solving NP‐hard problems in operations management and research, particularly in logistics, manufacturing, and finance. This study maps these applications to present a framework for future adoption across industries. ABSTRACT This study
Daniel Bouzon Nagem Assad +3 more
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Quantum approximate optimization for hard problems in linear algebra
SciPost Physics Core, 2021 The quantum approximate optimization algorithm (QAOA) by Farhi et al. is a quantum computational framework for solving quantum or classical optimization tasks.
Ajinkya Borle, Vincent E. Elfving, Samuel J. Lomonaco
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Enhancing Distributed State Estimation of Power Grid With a Simplified Quantum Algorithm
IET Generation, Transmission &Distribution, Volume 20, Issue 1, January/December 2026.This paper presents the application of the Harrow‐Hassidim‐Lloyd (HHL) algorithm and its simplified quantum circuit to distributed state estimation in power grids. The results show that the proposed approach successfully tackles distributed state estimation in a power grid, underscoring its potential as a practical quantum computing solution for this ...
Shyh‐Jier Huang +3 more
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IET Software, Volume 2026, Issue 1, 2026.Quantum computing is one of the research areas progressing rapidly toward practical deployment, yet the engineering of scalable and reliable quantum software remains underdeveloped. Current quantum software engineering (QSE) practices are largely tools‐driven and ad hoc that providing limited support for managing probabilistic execution, hybrid quantum–
Hessa Alfraihi +7 more
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Quantum approximate optimization via learning-based adaptive optimization
Communications PhysicsCombinatorial optimization problems are ubiquitous and computationally hard to solve in general. Quantum approximate optimization algorithm (QAOA), one of the most representative quantum-classical hybrid algorithms, is designed to solve combinatorial ...
Lixue Cheng +3 more
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Portfolio optimization with digitized counterdiabatic quantum algorithms
Physical Review Research, 2022 We consider digitized-counterdiabatic quantum computing as an advanced paradigm to approach quantum advantage for industrial applications in the NISQ era.
N. N. Hegade +5 more
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, 2016 We study a variant of the quantum approximate optimization algorithm [ E. Farhi, J. Goldstone, and S. Gutmann, arXiv:1411.4028] with slightly different parametrization and different objective: rather than looking for a state which approximately solves an
Hastings, M. B., Troyer, M., Wecker, D.
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Dynamic programming in economics on a quantum annealer
Quantitative Economics, Volume 17, Issue 1, Page 1-37, January 2026.We introduce novel algorithms for solving dynamic programming problems in economics on a quantum annealer, a specialized quantum computer used for combinatorial optimization. Quantum annealers begin in a superposition of all states and generate candidate global solutions in milliseconds, regardless of problem size.
Jesús Fernández‐Villaverde +1 more
wiley +1 more source
Investigating quantum approximate optimization algorithms under bang-bang protocols
Physical Review Research, 2020 The quantum approximate optimization algorithm (QAOA) is widely seen as a possible usage of noisy intermediate-scale quantum (NISQ) devices. We analyze the algorithm as a bang-bang protocol with fixed total time and a randomized greedy optimization ...
Daniel Liang +2 more
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