Benchmarking Zero-Setup Quantum Circuit Simulators

arXiv:2607.09882v2 Announce Type: replace Abstract: Practitioners increasingly rely on hosted simulation environments, but their performance characteristics remain poorly documented. We present a systematic benchmarking study of GPU-accelerated approximate quantum simulation across two widely used methods: matrix product states (MPS) and Pauli path simulation (PPS), comparing BlueQubit (a hosted tool that handles hardware provisioning, simulator configuration, and job orchestration) against AWS Braket, Quantum Rings, PPS-Qiskit, and PauliPropagation.jl. For MPS, we find that GPU runtime yields sub-quadratic scaling with bond dimension, with a growing advantage over CPU at increasing scale. For Pauli path simulation on IBM's 127-qubit kicked Ising benchmark, GPUs deliver up to $1{,}400\times$ speedup at fine truncation thresholds ($\delta = 2.5 \times 10^{-5}$, 27.6M Pauli terms), and are the only backends that reach accuracy regimes below $\delta = 10^{-5}$, which remained inaccessible to the commodity CPU-based implementations and self-contained SDKs evaluated here. We also provide a reproducible characterization of these simulators across regimes, including tradeoffs that isolated evaluations do not show. To support transparency and reuse, we provide a public GitHub repository containing all benchmarking code and configurations.

Abstract:Practitioners increasingly rely on hosted simulation environments, but their performance characteristics remain poorly documented. We present a systematic benchmarking study of GPU-accelerated approximate quantum simulation across two widely used methods: matrix product states (MPS) and Pauli path simulation (PPS), comparing BlueQubit (a hosted tool that handles hardware provisioning, simulator configuration, and job orchestration) against AWS Braket, Quantum Rings, PPS-Qiskit, and this http URL. For MPS, we find that GPU runtime yields sub-quadratic scaling with bond dimension, with a growing advantage over CPU at increasing scale. For Pauli path simulation on IBM's 127-qubit kicked Ising benchmark, GPUs deliver up to $1{,}400\times$ speedup at fine truncation thresholds ($\delta = 2.5 \times 10^{-5}$, 27.6M Pauli terms), and are the only backends that reach accuracy regimes below $\delta = 10^{-5}$, which remained inaccessible to the commodity CPU-based implementations and self-contained SDKs evaluated here. We also provide a reproducible characterization of these simulators across regimes, including tradeoffs that isolated evaluations do not show. To support transparency and reuse, we provide a public GitHub repository containing all benchmarking code and configurations.

Quantum Physics (quant-ph); Distributed, Parallel, and Cluster Computing (cs.DC); Performance (cs.PF)

arXiv:2607.09882 [quant-ph]

(or arXiv:2607.09882v2 [quant-ph] for this version)

https://doi.org/10.48550/arXiv.2607.09882 Focus to learn more arXiv-issued DOI via DataCite

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Benchmarking Zero-Setup Quantum Circuit Simulators

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