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Characterizing and Benchmarking Dynamic Quantum Circuits

arXiv Quantum Archived Apr 07, 2026 ✓ Full text saved

arXiv:2604.03360v1 Announce Type: new Abstract: Dynamic quantum circuits with mid-circuit measurements (MCMs) and feed-forward operations play a crucial role in various applications, such as quantum error correction and quantum algorithms. With advancements in quantum hardware enabling the implementation of MCM and feed-forward loops, the use of dynamic circuits has become increasingly prevalent. There is a significant need for a benchmarking framework specially designed for dynamic circuits to

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    Quantum Physics [Submitted on 3 Apr 2026] Characterizing and Benchmarking Dynamic Quantum Circuits Sumeet Shirgure, Efekan Kökcü, Anupam Mitra, Wibe Albert de Jong, Costin Iancu, Siyuan Niu Dynamic quantum circuits with mid-circuit measurements (MCMs) and feed-forward operations play a crucial role in various applications, such as quantum error correction and quantum algorithms. With advancements in quantum hardware enabling the implementation of MCM and feed-forward loops, the use of dynamic circuits has become increasingly prevalent. There is a significant need for a benchmarking framework specially designed for dynamic circuits to capture their unique properties, as current benchmarking tools are designed primarily for unitary circuits and cannot be trivially extended to dynamic circuits. We propose dynamarq, a scalable and hardware-agnostic benchmarking framework for dynamic circuits. We collect a set of dynamic circuit benchmarks spanning various applications and propose a broad set of circuit features to characterize the structure of these dynamic circuits. We run them on two IBM quantum processors and the Quantinuum Helios-1E emulator, and propose scalable, application-dependent fidelity scores for each benchmark based on hardware execution results. We perform statistical modeling to identify correlations between circuit features and fidelity scores, and demonstrate highly accurate fidelity prediction using our model. Our model parameters are also transferable across hardware backends and calibration cycles. Our framework facilitates the understanding of dynamic circuit structures and provides insights for designing and optimizing dynamic circuits to achieve high execution fidelity on quantum hardware. Subjects: Quantum Physics (quant-ph); Software Engineering (cs.SE) Cite as: arXiv:2604.03360 [quant-ph]   (or arXiv:2604.03360v1 [quant-ph] for this version)   https://doi.org/10.48550/arXiv.2604.03360 Focus to learn more Submission history From: Sumeet Shirgure [view email] [v1] Fri, 3 Apr 2026 17:31:12 UTC (624 KB) Access Paper: HTML (experimental) view license Current browse context: quant-ph < prev   |   next > new | recent | 2026-04 Change to browse by: cs cs.SE References & Citations INSPIRE HEP NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation 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 Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)
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    arXiv Quantum
    Category
    ◌ Quantum Computing
    Published
    Apr 07, 2026
    Archived
    Apr 07, 2026
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