Results 31 to 40 of about 25,693 (251)
Quantum Annealing for Clustering [PDF]
CoRR, 2009 8 pages, 6 figures, Proceedings of the 25th Conference on Uncertainty in Artificial Intelligence (UAI 2009 ...
Kenichi Kurihara +2 more
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Single-Qubit Fidelity Assessment of Quantum Annealing Hardware
IEEE Transactions on Quantum Engineering, 2021 As a wide variety of quantum computing platforms become available, methods for assessing and comparing the performance of these devices are of increasing interest and importance.
Jon Nelson +3 more
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Testing a Quantum Annealer as a Quantum Thermal Sampler [PDF]
ACM Transactions on Quantum Computing, 2021 Motivated by recent experiments in which specific thermal properties of complex many-body systems were successfully reproduced on a commercially available quantum annealer, we examine the extent to which quantum annealing hardware can reliably sample from the thermal state in a specific basis associated with a target quantum Hamiltonian.
Zoe Gonzalez Izquierdo +2 more
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Learning-Driven Annealing with Adaptive Hamiltonian Modification for Solving Large-Scale Problems on Quantum Devices [PDF]
QuantumWe present Learning-Driven Annealing (LDA), a framework that links individual quantum annealing evolutions into a global solution strategy to mitigate hardware constraints such as short annealing times and integrated control errors.
Sebastian Schulz +2 more
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Quantum annealing for combinatorial clustering [PDF]
Quantum Information Processing, 2018 Clustering is a powerful machine learning technique that groups "similar" data points based on their characteristics. Many clustering algorithms work by approximating the minimization of an objective function, namely the sum of within-the-cluster distances between points.
Vaibhaw Kumar +3 more
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Quantum Speedup by Quantum Annealing
Physical Review Letters, 2012 We study the glued-trees problem of Childs et. al. in the adiabatic model of quantum computing and provide an annealing schedule to solve an oracular problem exponentially faster than classically possible. The Hamiltonians involved in the quantum annealing do not suffer from the so-called sign problem.
Nagaj, Daniel +2 more
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How to Solve Combinatorial Optimization Problems Using Real Quantum Machines: A Recent Survey
IEEE Access, 2022 A combinatorial optimization problem (COP) is the problem of finding the optimal solution in a finite set. When the size of the feasible solution set is large, the complexity of the problem increases, and it is not easy to solve in a reasonable time with
Sovanmonynuth Heng +3 more
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CoRR, 2014 Brief description on the state of the art of some local optimization methods: Quantum annealing Quantum annealing (also known as alloy, crystallization or tempering) is analogous to simulated annealing but in substitution of thermal activation by quantum tunneling.
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Travel time optimization on multi-AGV routing by reverse annealing
Scientific Reports, 2022 Quantum annealing has been actively researched since D-Wave Systems produced the first commercial machine in 2011. Controlling a large fleet of automated guided vehicles is one of the real-world applications utilizing quantum annealing. In this study, we
Renichiro Haba +2 more
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Quantum Annealing of a Disordered Magnet [PDF]
Science, 1999 Traditional simulated annealing uses thermal fluctuations for convergence in optimization problems. Quantum tunneling provides a different mechanism for moving between states, with the potential for reduced time scales. Thermal and quantum annealing are compared in a model disordered magnet, where the effects of quantum mechanics can be tuned by ...
J. Brooke +4 more
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