Abstract:

A quantum convolution circuit model that encodes one-dimensional information into a quantum state and inputs the quantum state into a quantum circuit for convolution calculation is researched. Based on quantum image representation and classical information convolution algorithm, the quantum circuit structure of one-dimensional quantum convolution calculation is designed. The results show that quantum convolution calculation can reduce the computational complexity of convolution calculation. Compared with classical convolution, quantum convolution calculation speeds up the calculation by using quantum parallel computing, paving the way for the convolutional layer design of quantum convolutional neural networks.

Key words: quantum gate, convolution calculation, quantum circuit

摘要：

研究了一维信息编码为量子态后进行量子卷积计算的量子线路模型。基于量子图像表示和经典信息的卷积算法，设计出了一维量子卷积计算的量子线路结构，表明量子卷积计算可以以[O(n2)]的复杂度计算卷积。与经典卷积相比，量子卷积计算由于利用量子并行计算在计算速率上达到了指数级的加速，为量子卷积神经网络卷积层的设计实施作铺垫。

关键词: 量子门, 卷积计算, 量子线路