Quantum annealing, or quantum stochastic optimization, is a classical randomized algorithm which provides good heuristics for the solution of hard optimization problems. The algorithm, suggested by the behaviour of quantum systems, is an example of proficuous cross contamination between classical and quantum computer science. In this survey paper we illustrate how hard combinatorial problems are tackled by quantum computation and present some examples of the heuristics provided by quantum annealing. We also present preliminary results about the application of quantum dissipation (as an alternative to imaginary time evolution) to the task of driving a quantum system toward its state of lowest energy.

An introduction to quantum annealing / D. de Falco, D. Tamascelli. - In: RAIRO. INFORMATIQUE THEORIQUE ET APPLICATIONS. - ISSN 0988-3754. - 45:1(2011 Jan), pp. 99-116. [10.1051/ita/2011013]

An introduction to quantum annealing

D. de Falco
Primo
;
D. Tamascelli
Ultimo
2011

Abstract

Quantum annealing, or quantum stochastic optimization, is a classical randomized algorithm which provides good heuristics for the solution of hard optimization problems. The algorithm, suggested by the behaviour of quantum systems, is an example of proficuous cross contamination between classical and quantum computer science. In this survey paper we illustrate how hard combinatorial problems are tackled by quantum computation and present some examples of the heuristics provided by quantum annealing. We also present preliminary results about the application of quantum dissipation (as an alternative to imaginary time evolution) to the task of driving a quantum system toward its state of lowest energy.
Adiabatic quantum computation; Combinatorial optimization; Dissipative dynamics; Quantum annealing
Settore INF/01 - Informatica
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/160702
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