QMClaw: A Scalable General-purpose Framework for Quantum Measurement and Control
Abstract
As quantum computing continues to scale, quantum measurement and control (QMC) are increasingly constrained by calibration workflow complexity and by requirements for low-latency execution, robust exception handling, and traceable workflow governance. Existing frameworks for QMC are specialized and task-specific, while language-model-based agents for QMC suffer from excessive latency and cannot satisfy the strict timing and control-density demands of large-scale quantum systems. Here we propose QMClaw, a general, workflow-oriented framework for QMC built, featuring a local-first, tool-governed, robust architecture. At its core is a RuleEngine-centered control layer that processes structured context, performs rule-based state transitions, and generates execution plans for typical calibration workflows. Language models are used only for natural-language interaction, high-level task understanding, and exception support, keeping the critical fast path efficient. We implement a single qubit tune-up workflow as a demonstration and validation using real quantum device dataset. We also prove that the framework achieves quantitatively acceptable levels in terms of resource cost, LLM calling times and decision latency, enabling its practical deployment in large-scale quantum qubit measurement and control scenarios. This work presents a general workflow-oriented framework for QMC and provides evidence that rule-centered architectures are a promising design choice for scalable quantum-system calibration.
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BibTeX
@misc{fan2026qmclaw,
title = {{QMClaw: A Scalable General-purpose Framework for Quantum Measurement and Control}},
author = {Zhiqiang Fan and Haoran He and Ping Lv and Junchao Wang and Yaqiang Sun and Chenhui Wang and Hanshi Zhao and Geyuyan Ma and Haoran Yang and Pengyu Han and Xiangdong Meng and Lixin Wang and Feng Yue and Weilong Wang and Zheng Shan},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.04674},
eprint = {2609.04674},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.04674},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - QMClaw: A Scalable General-purpose Framework for Quantum Measurement and Control
AU - Zhiqiang Fan
AU - Haoran He
AU - Ping Lv
AU - Junchao Wang
AU - Yaqiang Sun
AU - Chenhui Wang
AU - Hanshi Zhao
AU - Geyuyan Ma
AU - Haoran Yang
AU - Pengyu Han
AU - Xiangdong Meng
AU - Lixin Wang
AU - Feng Yue
AU - Weilong Wang
AU - Zheng Shan
PY - 2026
DA - 2026/09/04
PB - arXiv
DO - 10.48550/arxiv.2609.04674
UR - https://arxiv.org/abs/2609.04674
AB - As quantum computing continues to scale, quantum measurement and control (QMC) are increasingly constrained by calibration workflow complexity and by requirements for low-latency execution, robust exception handling, and traceable workflow governance. Existing frameworks for QMC are specialized and task-specific, while language-model-based agents for QMC suffer from excessive latency and cannot satisfy the strict timing and control-density demands of large-scale quantum systems. Here we propose QMClaw, a general, workflow-oriented framework for QMC built, featuring a local-first, tool-governed, robust architecture. At its core is a RuleEngine-centered control layer that processes structured context, performs rule-based state transitions, and generates execution plans for typical calibration workflows. Language models are used only for natural-language interaction, high-level task understanding, and exception support, keeping the critical fast path efficient. We implement a single qubit tune-up workflow as a demonstration and validation using real quantum device dataset. We also prove that the framework achieves quantitatively acceptable levels in terms of resource cost, LLM calling times and decision latency, enabling its practical deployment in large-scale quantum qubit measurement and control scenarios. This work presents a general workflow-oriented framework for QMC and provides evidence that rule-centered architectures are a promising design choice for scalable quantum-system calibration.
ER -