  Quantum computing was so far mainly concerned with discrete problems.
  Recently, E. Novak and the author studied quantum algorithms for high
dimensional integration and dealt with the question, which advantages quantum
computing can bring over classical deterministic or randomized methods for this
type of 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.
