New Applications of Random Sampling in Computational Geometry.
Noise effects in the quantum search algorithm from the viewpoint of computational complexity
We analyse the resilience of the quantum search algorithm in the presence of quantum noise modelled as trace preserving completely positive maps. We study the influence of noise on the computational complexity of the quantum search algorithm. We show that it is only for small amounts of noise that the quantum search algorithm is still more efficient than any classical algorithm.
Numerical studies of the asymptotic height distribution in binary search trees.