There are many challenges involved in building near-term large-scale quantum computers. Some of these challenges can be overcome by partitioning a quantum circuit into smaller parts and allowing each part to be executed on a smaller quantum unit. This approach is known as distributed quantum computation. In this study, a dynamic programming algorithm is proposed to minimize the number of communications in a distributed quantum circuit. This algorithm consists of two steps: first, the quantum circuit is converted into a bipartite graph model, and then a dynamic programming approach is proposed to partition the model into low-capacity quantum circuits. The proposed approach is evaluated on some benchmark quantum circuits, and a remarkable reduction in the number of required teleportations is obtained.

建立近期的大规模量子计算机涉及许多挑战。通过将量子电路划分为较小的部分并允许每个部分在较小的量子单元上执行，可以克服其中的一些挑战。这种方法称为分布式量子计算。在这项研究中，提出了一种动态编程算法以最小化分布式量子电路中的通信数量。该算法包括两个步骤：首先，将量子电路转换为二部图模型，然后提出一种动态规划方法，将模型划分为低容量量子电路。在某些基准量子电路上对提出的方法进行了评估，并显着减少了所需的隐形传态次数。