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Benchmarking Zero-Setup Quantum Circuit Simulators

Arul Rhik Mazumder, Mohammed Zuhair Mullath, Hayk Tepanyan
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--> Quantum Physics arXiv:2607.09882 (quant-ph) [Submitted on 10 Jul 2026] Title:Benchmarking Zero-Setup Quantum Circuit Simulators Authors:Arul Rhik Mazumder, Mohammed Zuhair Mullath, Hayk Tepanyan View a PDF of the paper titled Benchmarking Zero-Setup Quantum Circuit Simulators, by Arul Rhik Mazumder and 2 other authors View PDF HTML (experimental) Abstract:Practitioners increasingly rely on hosted simulation environments, but their performance characteristics remain poorly documented.
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Quantum Physics arXiv:2607.09882 (quant-ph) [Submitted on 10 Jul 2026] Title:Benchmarking Zero-Setup Quantum Circuit Simulators Authors:Arul Rhik Mazumder, Mohammed Zuhair Mullath, Hayk Tepanyan View a PDF of the paper titled Benchmarking Zero-Setup Quantum Circuit Simulators, by Arul Rhik Mazumder and 2 other authors View PDF HTML (experimental) 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. Comments: Subjects: Quantum Physics (quant-ph); Distributed, Parallel, and Cluster Computing (cs.DC); Performance (cs.PF) Cite as: arXiv:2607.09882 [quant-ph] (or arXiv:2607.09882v1 [quant-ph] for this version) https://doi.org/10.48550/arXiv.2607.09882 Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Arul Mazumder [view email] [v1] Fri, 10 Jul 2026 18:15:12 UTC (2,083 KB) Full-text links: Access Paper: View a PDF of the paper titled Benchmarking Zero-Setup Quantum Circuit Simulators, by Arul Rhik Mazumder and 2 other authorsView PDFHTML (experimental)TeX Source view license Current browse context: quant-ph new | recent | 2026-07 Change to browse by: cs cs.DC cs.PF References & Citations INSPIRE HEP NASA ADSGoogle Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... Data provided by: Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv (What is alphaXiv?) Links to Code Toggle CatalyzeX Code Finder for Papers (What is CatalyzeX?) DagsHub Toggle DagsHub (What is DagsHub?) GotitPub Toggle Gotit.pub (What is GotitPub?) Huggingface Toggle Hugging Face (What is Huggingface?) ScienceCast Toggle ScienceCast (What is ScienceCast?) Demos Demos Replicate Toggle Replicate (What is Replicate?) Spaces Toggle Hugging Face Spaces (What is Spaces?) Spaces Toggle TXYZ.AI (What is TXYZ.AI?) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower (What are Influence Flowers?) Core recommender toggle CORE Recommender (What is CORE?) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs. Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)

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