Quantum set intersection and its application to associative memory
The Journal of Machine Learning Research
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For searching an unsorted database with N items, a classical computer requires O(N) steps but Grover's quantum searching algorithm requires only O(√N) steps. However, it is also known that Grover's algorithm is effective in the case where the initial amplitude distribution of dataset is uniform, but is not always effective in the non-uniform case.In this paper, we will consider the influence of initial amplitude distribution of dataset for Grover's and Ventura's algorithms. Further, in order to improve the performance of quantum searching, we propose a new algorithm and analyze its dynamics.