为了解决量子电路在线性近邻化过程中的电路综合与量子代价优化问题,提出了一种 考虑前瞻影响因素的线性最近邻量子电路综合与优化算法。该算法对任意给定的非最近邻量子 电路,通过分别度量不同方法下操作当前量子门的过程对其后量子门的最近邻量子代价造成的 影响,降低相邻量子门近邻化过程所需的SWAP门数量,从而达到构建并优化线性最近邻量子电 路的要求。采用具有代表性的Benchmark例题进行实验,并以具有代表性和可比性的文献结论作 为比较对象,对线性最近邻电路逻辑综合算法的结果进行了比较,结果表明所提出优化算法在添加 交换门增量上有较大改进, 22例Benchmark例题正优化达到18例,占比81.82%, 平均正优化率 为18.32%, 平均优化率为11.75%。

To resolve the problem of circuit synthesis and quantum cost optimization in linear nearest neighboring of quantum circuits, an algorithm considering look-ahead influencing factors for synthesizing and optimizing the linear nearest neighbor quantum circuit is proposed. For any given non-nearest neighbor quantum circuit, the algorithm can separately measure the impact of operating the current quantum gate with different methods on the nearest neighbor cost of the subsequent quantum gate and reduce the number of SWAP gates required for the near-neighboring process of adjacent quantum gates. Thus, the requirements of constructing and optimizing linear nearest neighbor quantum circuits can be achieved. Experiments are conducted with the typical Benchmark examples, and the results of the logic synthesis algorithms for linear nearest neighbor circuit are compared among the representative and comparable research findings. Results show that the proposed optimization algorithm makes a great improvement in adding the incremental SWAP gates. Among the 22 Benchmark examples, 18(81.82%) are positively optimized, with an average positive optimization rate of 18.32%, and an average optimization rate of 11.75%.