Current quantum computer designs will not scale. To scale beyond small prototypes, quantum architectures will likely adopt a modular approach with clusters of tightly connected quantum bits and sparser connections between clusters. We exploit this clustering and the statically-known control flow of quantum programs to create tractable partitioning heuristics which map quantum circuits to modular physical machines one time slice at a time. Specifically, we create optimized mappings for each time slice, accounting for the cost to move data from the previous time slice and using a tunable lookahead scheme to reduce the cost to move to future time slices. We compare our approach to a traditional statically-mapped, owner-computes model. Our results show strict improvement over the static mapping baseline. We reduce the non-local communication overhead by 89.8\% in the best case and by 60.9\% on average. Our techniques, unlike many exact solver methods, are computationally tractable.

中文翻译：

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模块化架构的时间切片量子电路分区

当前的量子计算机设计不会扩展。为了超越小型原型，量子架构可能会采用模块化方法，其中包含紧密连接的量子位集群和集群之间的稀疏连接。我们利用这种集群和量子程序的静态已知控制流来创建易于处理的分区启发式，将量子电路一次一个时间片映射到模块化物理机器。具体来说，我们为每个时间片创建优化映射，考虑从前一个时间片移动数据的成本，并使用可调整的前瞻方案来降低移动到未来时间片的成本。我们将我们的方法与传统的静态映射、所有者计算模型进行比较。我们的结果显示了对静态映射基线的严格改进。我们在最佳情况下将非本地通信开销减少了 89.8\%，平均减少了 60.9\%。与许多精确求解器方法不同，我们的技术在计算上易于处理。