Distributed Quantum Circuit Optimisation: Evaluating Global and Local encodings

TL;DR

This paper evaluates how different quantum circuit optimisation strategies impact distributed quantum workloads, balancing computational, communication, and preprocessing costs.

Contribution

It compares global, local, and hybrid optimisation approaches for distributed quantum circuits, highlighting their trade-offs in resource use and overhead.

Findings

Global optimisation minimizes computational resources and compilation overhead.

Local optimisation reduces communication costs without explicit communication-awareness.

Hybrid approach balances resource reduction but increases compilation time.

Abstract

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.