Effects of initial states on the quantum correlations in the generalized Grover search algorithm*

Abstract

We investigate the correlations between two qubits in the Grover search algorithm with arbitrary initial states by numerical simulation. Using a set of suitable bases, we construct the reduced density matrix and give the numerical expression of correlations relating to the iterations. For different initial states, we obtain the concurrence and quantum discord compared with the success probability in the algorithm. The results show that the initial states affect the correlations and the limit point of the correlations in the searching process. However, the initial states do not influence the whole cyclical trend.

Binary Classification Quantum Neural Network Model Based on Optimized Grover Algorithm

“…Big data provides a new way of thinking and a new means for exploring objective laws and for transforming nature and society for human beings. Due to the high and increasing demand for big data mining and analysis work, the era is forced to gradually use more efficient quantum scientific research technology [ 15 ] to meet the gap of technology improvement means, and then to improve the efficiency of information extraction work and to promote the progress of more scientific research. In view of the above requirements and improved thinking, this paper makes use of the special advantages of quantum algorithms compared with traditional iterative algorithms [ 16 ], as a new field of quantum neural network, and studies the neural network autonomous learning scheme [ 17 ] for network log information extraction, which highlights the high-value prospects of the quantum field in big data mining and analysis.…”