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.
@article{ITA_2011__45_1_99_0,
author = {de Falco, Diego and Tamascelli, Dario},
title = {An introduction to quantum annealing},
journal = {RAIRO - Theoretical Informatics and Applications - Informatique Th\'eorique et Applications},
volume = {45},
year = {2011},
pages = {99-116},
doi = {10.1051/ita/2011013},
mrnumber = {2776856},
zbl = {1219.68105},
language = {en},
url = {http://dml.mathdoc.fr/item/ITA_2011__45_1_99_0}
}
de Falco, Diego; Tamascelli, Dario. An introduction to quantum annealing. RAIRO - Theoretical Informatics and Applications - Informatique Théorique et Applications, Tome 45 (2011) pp. 99-116. doi : 10.1051/ita/2011013. http://gdmltest.u-ga.fr/item/ITA_2011__45_1_99_0/
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