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This research introduces Quantum-Harbor and QIQCBench, frameworks designed to rigorously verify the reliability of AI agents operating within complex quantum engineering environments. By benchmarking 17 frontier agentic systems across tasks like error correction and calibration, the study highlights a critical gap between demonstrated capability and consistent, reliable autonomous operation. These tools establish a necessary foundation for measuring progress toward fully autonomous quantum system management.
Surse care acoperăarXiv, Quantum Computing Report, LessWrong, SiliconANGLE
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Evaluating Verified Autonomy in Quantum Engineering

arXiv2 min de cititArticolul și perspectiva sunt în engleză.

arXiv:2609.17439v1 Announce Type: new Abstract: Reliable quantum engineering is essential for turning quantum phenomena into practical technologies. As quantum platforms grow in scale and complexity, their characterization and operation require increasing human effort and coordination. Scientific artificial intelligence agents, which can plan experiments, operate instruments, and analyze observations, offer a promising route towards autonomous quantum engineering. Yet whether current agents can perform reliably in this setting has not been systematically established. To fill this gap, we developed Quantum-Harbor, a virtual laboratory that provides a controlled execution environment for agents to interact with quantum systems. This design enables direct verification of both the actions taken and the conclusions drawn. Building on this framework, we introduce QIQCBench, a benchmark of $49$ expert-authored tasks spanning multiple layers including calibration and control, error correction and compilation, sensing and networking. Across $17$ frontier agentic systems, QIQCBench reveals wide variation in verified performance. These results expose a substantial gap between demonstrating capability and achieving reliable operation, and establish Quantum-Harbor as a foundation for measuring progress towards verified autonomy in quantum engineering.

Abstract:Reliable quantum engineering is essential for turning quantum phenomena into practical technologies. As quantum platforms grow in scale and complexity, their characterization and operation require increasing human effort and coordination. Scientific artificial intelligence agents, which can plan experiments, operate instruments, and analyze observations, offer a promising route towards autonomous quantum engineering. Yet whether current agents can perform reliably in this setting has not been systematically established. To fill this gap, we developed Quantum-Harbor, a virtual laboratory that provides a controlled execution environment for agents to interact with quantum systems. This design enables direct verification of both the actions taken and the conclusions drawn. Building on this framework, we introduce QIQCBench, a benchmark of $49$ expert-authored tasks spanning multiple layers including calibration and control, error correction and compilation, sensing and networking. Across $17$ frontier agentic systems, QIQCBench reveals wide variation in verified performance. These results expose a substantial gap between demonstrating capability and achieving reliable operation, and establish Quantum-Harbor as a foundation for measuring progress towards verified autonomy in quantum engineering.

Quantum Physics (quant-ph); Artificial Intelligence (cs.AI)

arXiv:2609.17439 [quant-ph]

(or arXiv:2609.17439v1 [quant-ph] for this version)

https://doi.org/10.48550/arXiv.2609.17439 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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