Abstract:To solve the problems in the traditional quantum circuit scheduling algorithms in terms of scheduling quality, diversity, and adaptability to complex quantum circuit structures, this study proposes a layered quantum circuit scheduling and ant colony optimization (LQCS-ACO) fusion algorithm. By combining the layered quantum circuit scheduling and ant colony algorithm, and comprehensively considering multiple factors such as the layer dependency relationship between quantum gates, the number of SWAP gate operations, the number of CNOT gates, and the number of circuit layers, a fitness function suitable for the quantum circuit layer structure is designed. Meanwhile, a dynamic pheromone adjustment mechanism based on the feedback of quantum circuit layers is adopted to reduce the risk of the algorithm falling into a local optimum. Meanwhile, an inter-layer pheromone transmission method is introduced. By considering the influence of quantum circuit layers, the inter-layer transmission of scheduling information is completed, and the efficiency of the overall scheduling scheme and the global optimization effect are improved. Experimental results show that in the 2QAN quantum circuit scheduling process, compared with the 2QAN circuit, HQAA algorithm, and ACO algorithm, the number of inserted SWAP gates of LQCS-ACO is reduced by 5.8%, 8.3%, and 7.3% respectively, and the number of CNOT gates decreases by 8.2%, 9.2%, and 33.8% respectively.