In this paper, we formally describe the three challenges of mapping surface code on superconducting devices, and present a comprehensive synthesis framework to overcome these challenges. The proposed framework consists of three optimizations. First, we adopt a geometrical method to allocate data qubits which ensures the existence of shallow syndrome extraction circuit. The proposed data qubit layout optimization reduces the overhead of syndrome extraction and serves as a good initial point for following optimizations. Second, we only use bridge qubits enclosed by data qubits and reduce the number of bridge qubits by merging short path between data qubits. The proposed bridge qubit optimization reduces the probability of bridge qubit conflicts and further minimizes the syndrome extraction overhead. Third, we propose an efficient heuristic to schedule syndrome extractions. Based on the proposed data qubit allocation, we devise a good initial schedule of syndrome extractions and further refine this schedule to minimize the total time needed by a complete surface code error detection cycle. Our experiments on mainsstream superconducting quantum architectures have demonstrated the efficiency of the proposed framework.
翻译:在本文中,我们正式描述了绘制超导装置表面代码的三项挑战,并提出了一个全面的综合框架来克服这些挑战。拟议框架包括三个优化。首先,我们采用了几何方法来分配确保存在浅度综合症提取电路的数据 ⁇ 。拟议数据qubit版面优化减少了综合症提取的间接结果,并成为了最佳优化的起始点。第二,我们只使用数据qubit的连接桥基点,并通过将数据qubit之间的短路合并来减少桥基点数量。拟议的桥基点优化降低了桥基点冲突的可能性,并进一步将综合症提取间接费用降到最低程度。第三,我们建议对综合症提取工作进行高效的超常量化。根据拟议数据qubit的配置,我们设计了一个良好的综合症提取初步时间表,并进一步完善这一时间表,以最大限度地减少完整地表代码错误检测周期所需的全部时间。我们在主流超导量结构上进行的实验证明了拟议框架的效率。