Abstract
Quantum computing was so far mainly concerned with discrete problems. Recently, Novak and the author studied quantum algorithms for high dimensional integration and dealt with the question, what advantages quantum computing can bring over classical deterministic or randomized methods for this type of a problem. In this paper we give a short introduction to the basic ideas of quantum computing and survey recent results on high dimensional integration. We discuss connections to the Monte Carlo methology and compare the optimal error rates of quantum algorithms to those of classical deterministic and randomized algorithms.
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