As distributed quantum architectures begin to emerge, understanding the interaction between quantum circuit optimisation and circuit partitioning becomes increasingly important. In this work, we study how circuit optimisation influences distributed quantum workloads under system-level trade-offs. We compare three compilation strategies (global optimisation, local optimisation, and a hybrid approach) across a large benchmark suite of quantum algorithms. Using telegate-based partitioning, we evaluate the resulting distributed circuits in terms of gate counts, circuit depth, the number of induced non-local gates, and compilation overhead, thereby approximating computational, communication, and classical preprocessing costs. Our results show that circuit optimisation does not uniformly benefit distributed execution. Global optimisation minimises computational resources and achieves the lowest compilation overhead. Local optimisation can reduce communication cost even though it is not explicitly communication-aware. The hybrid strategy can simultaneously reduce both computational and communication overhead, but at the expense of significantly increased compilation time.

翻译：随着分布式量子架构开始出现，理解量子电路优化与电路划分之间的相互作用变得愈发重要。本文研究了在系统级权衡条件下，电路优化如何影响分布式量子工作负载。我们比较了三种编译策略（全局优化、局部优化和混合方法），并在大量量子算法基准测试集上进行评估。采用基于电报的分区方法，我们通过门数量、电路深度、诱导的非局部门数量以及编译开销来评估生成的分布式电路，从而近似计算、通信和经典预处理成本。结果表明，电路优化并不能一致地有益于分布式执行。全局优化最小化计算资源并实现最低的编译开销。局部优化可以降低通信成本，即使它并非明确地考虑通信因素。混合策略能同时减少计算和通信开销，但代价是编译时间显著增加。