抄録
A study on optimization behavior by an alternative quantum algorithm for combinatorial search is presented. The algorithm operates with superpositions of all possible search states for an NP-Hard. Each of their steps consists of shifting the phases of the amplitudes in the super -positions based on the properties of the problem being solved, combined with problem-independent operation to mix amplitudes among different states. Simulations with randomly generated instances have shown each step shifts the amplitude toward lower cost states on average. These results are compared with conventional heuristics “Genetic algorithm” for the same instances.
