An End-to-End Distributed Quantum Circuit Simulator

Fuente: arXiv
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Main Authors: Zhang, Sen, Xiong, Lingjun, Liu, Yipie, Mark, Brian L., Yang, Lei, Yang, Zebo, Jiang, Weiwen
Format: Preprint
Published: 2025
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author Zhang, Sen
Xiong, Lingjun
Liu, Yipie
Mark, Brian L.
Yang, Lei
Yang, Zebo
Jiang, Weiwen
author_facet Zhang, Sen
Xiong, Lingjun
Liu, Yipie
Mark, Brian L.
Yang, Lei
Yang, Zebo
Jiang, Weiwen
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2511_19791
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle An End-to-End Distributed Quantum Circuit Simulator
Zhang, Sen
Xiong, Lingjun
Liu, Yipie
Mark, Brian L.
Yang, Lei
Yang, Zebo
Jiang, Weiwen
Emerging Technologies
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.
title An End-to-End Distributed Quantum Circuit Simulator
topic Emerging Technologies
url https://arxiv.org/abs/2511.19791