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的出现，理解量子电路优化与电路划分之间的相互作用日益重要。本研究深入探讨了在系统级权衡下，电路优化如何影响分布式量子工作负载。我们通过一个大规模量子算法基准测试套件，比较了三种编译策略（全局优化、局部优化及混合方法）。基于远程门划分，我们评估了所得分布式电路的门数、电路深度、诱导的非局部门数量及编译开销，从而近似表征计算、通信及经典预处理成本。研究结果表明，电路优化并非始终有益于分布式执行。全局优化最小化计算资源并实现最低编译开销；局部优化虽未显式考虑通信，却能降低通信成本；混合策略可同时降低计算与通信开销，但代价是编译时间显著增加。