Аннотации:
© Medwell Journals, 2017.Hashing is a widely used technique in computer science. The recently proposed quantum hashing has also proved its usefulness in a number of applications. The key property of both classical and quantum hashing is the ability to withstand collisions however, the notion of collision itself is different in the classical and quantum setting. In this study we analyze the set of numeric parameters that determine the probability of quantum collisions for the quantum hashing. Although, there is a general method of obtaining good hashing parameters, it makes sense for comparatively large inputs. That is why we construct different methods to complement the general one. We present two explicit optimization algorithms for computation of quantum hashing parameters: one is based on the genetic approach and the other uses the annealing simulation. The solution to the considered optimization problem can be used for the variety of quantum hash functions and also provides a solution to the general problem of constructing sets of pairwise distinguishable states in low-dimensional spaces.
