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Quantum annealing

Known as: Annealing 
Quantum annealing (QA) is a metaheuristic for finding the global minimum of a given objective function over a given set of candidate solutions… Expand
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Papers overview

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Highly Cited
2018
Highly Cited
2018
In this work we perform numerical simulations of a quantum annealing procedure to find the ground state of a target Hamiltonian… Expand
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Highly Cited
2017
Highly Cited
2017
Quantum annealing algorithms belong to the class of meta-heuristic tools, applicable for solving binary optimization problems… Expand
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2017
2017
I describe how real quantum annealers may be used to perform local (in state space) searches around specified states, rather than… Expand
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Highly Cited
2016
Highly Cited
2016
Inspired by the success of Boltzmann Machines based on classical Boltzmann distribution, we propose a new machine learning… Expand
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2016
2016
Can quantum computers solve optimization problems much more quickly than classical computers? One major piece of evidence for… Expand
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Highly Cited
2014
Highly Cited
2014
Quantum annealing is expected to solve certain optimization problems more efficiently, but there are still open questions… Expand
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Highly Cited
2014
Highly Cited
2014
Abstract : Entanglement lies at the core of quantum algorithms designed to solve problems that are intractable by classical… Expand
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Highly Cited
2014
Highly Cited
2014
Recently, a programmable quantum annealing machine has been built that minimizes the cost function of hard optimization problems… Expand
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Highly Cited
2011
Highly Cited
2011
Quantum annealing extends simulated annealing by introducing artificial quantum fluctuations. The path-integral Monte Carlo… Expand
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Highly Cited
1998
Highly Cited
1998
We introduce quantum fluctuations into the simulated annealing process of optimization problems, aiming at faster convergence to… Expand
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