An End-to-End Distributed Quantum Circuit Simulator

TL;DR

The paper tackles the lack of circuit-level simulators for distributed quantum computing that can model heterogeneous backends, inter-QPU communication, and distributed execution. It introduces SimDisQ, an end-to-end DQC simulator with four core toolkits—topology-aware constructor, backend-specific isolator, deadlock-free assembler, and communication-integrated noise model—that integrate with existing quantum software ecosystems. Through noise-free validation on six representative circuits and data-center-scale benchmarking across five architectures, SimDisQ demonstrates that heterogeneous multi-QPU configurations can achieve higher fidelity than monolithic, noisier backends and highlights the critical trade-offs in topology, resources, and noise. The framework enables co-design of hardware, network topology, and compilation strategies for emerging DQC systems, providing a practical foundation for future distributed quantum computing research.

Abstract

Quantum computing has made substantial progress in recent years; however, its scalability remains constrained on a monolithic quantum processing unit (QPU). Distributed quantum computing (DQC) offers a pathway by coordinating multiple QPUs to execute large-scale circuits. Yet, DQC still faces practical barriers, as its realization depends on advances in hardware-level components such as quantum transducers and high-fidelity entanglement-distribution modules. While these technologies continue to improve, mature DQC platforms remain unavailable. In the meantime, researchers need to assess the benefits of DQC and evaluate emerging DQC designs, but the software ecosystem lacks a circuit-level simulator that models heterogeneous backends, noisy connections, and distributed execution. To fill this gap, this paper proposes SimDisQ, the first end-to-end circuit-level DQC simulator, composed of a set of novel DQC-oriented automated simulation toolkits and communication noise models that can interoperate with existing toolkits in mainstream quantum software ecosystems. Leveraging circuit-level simulation capabilities, SimDisQ enables quantitative exploration of architectural design trade-offs, communication fidelity constraints, and new circuit optimization challenges introduced by DQC, providing a foundation for future research in this promising direction. Benchmarking experiments using SimDisQ respond to a couple of open questions in the community; for example, noisy simulation of superconducting and trapped-ion qubits, with a reasonable entanglement-distribution fidelity, reveal that heterogeneous QPUs can indeed yield higher execution fidelity.

Figures (6)

• Figure 1: Overview of the SimDisQ Framework.
• Figure 2: Illustration of the proposed five-step constructor.
• Figure 3: Illustration of the proposed sub-circuits isolator.
• Figure 4: Workflow of assembler from transpiled subcircuits to a DQC circuit (DQC-C) with correct execution trace.
• Figure 5: Fidelity results across all benchmarks and architectures with an inter-QPU distance of 0.2km for data-center scale.