多目标精确量子搜索算法的优化及实现OA

An optimized iterative operator is constructed by leveraging quantum rotation gates,an improved multi-target exact search algorithm is proposed,and simulation experiments of the optimized multi-target search algorithm are conducted on the quantum computing platform MindQuantum.The results demonstrate that,in comparison with the Grover's algorithm and the Long's algorithm,the optimized multi-target search algorithm reduces the number of quantum gates by up to 35.4％and the circuit depth by up to 17.8％while maintaining a 100％success rate.In addition,the noise suppression of the optimized algorithm is investigated by introducing the depolarizing channel.The results indicate that under the same noise conditions,the proposed algorithm consistently outperforms the Grover's algorithm and the Long's algorithm in terms of search success rate,exhibiting superior noise suppression capacity.