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An introduction to quantum annealing

Published online by Cambridge University Press:  15 March 2011

Diego de Falco  and
Dario Tamascelli
Diego de Falco
Affiliation:
Dipartimento di Scienze dell'Informazione Università degli Studi di Milano, via Comelico 39/41, 20135 Milano, Italy; tamascelli@dsi.unimi.it
Dario Tamascelli
Affiliation:
Dipartimento di Scienze dell'Informazione Università degli Studi di Milano, via Comelico 39/41, 20135 Milano, Italy; tamascelli@dsi.unimi.it
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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.

Keywords

Combinatorial optimizationadiabatic quantum computationquantum annealingdissipative dynamics

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Type
Research Article
Information
RAIRO - Theoretical Informatics and Applications , Volume 45 , Issue 1: ICTCS 09 , January 2011 , pp. 99 - 116
Copyright
© EDP Sciences, 2011

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