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[2602.23085] Q-Tag: Watermarking Quantum Circuit Generative Models
Summary
The paper presents Q-Tag, a novel watermarking framework for quantum circuit generative models (QCGMs), addressing the need for secure copyright protection in automated quantum circuit design.
Why It Matters
As quantum cloud platforms gain traction, protecting intellectual property in quantum circuits becomes crucial. This framework integrates watermarking directly into the generative process, enhancing security against unauthorized use while maintaining circuit fidelity, which is vital for the future of quantum computing.
Key Takeaways
- Introduces a watermarking framework for quantum circuit generative models.
- Integrates watermarking into the generation process for enhanced security.
- Achieves high-fidelity circuit generation while preserving ownership signals.
- Addresses limitations of existing watermarking methods in generative settings.
- Empirical results demonstrate robustness against adversarial attacks.
Quantum Physics arXiv:2602.23085 (quant-ph) [Submitted on 26 Feb 2026] Title:Q-Tag: Watermarking Quantum Circuit Generative Models Authors:Yang Yang, Yuzhu Long, Han Fang, Zhaoyun Chen, Zhonghui Li, Weiming Zhang, Guoping Guo View a PDF of the paper titled Q-Tag: Watermarking Quantum Circuit Generative Models, by Yang Yang and 6 other authors View PDF HTML (experimental) Abstract:Quantum cloud platforms have become the most widely adopted and mainstream approach for accessing quantum computing resources, due to the scarcity and operational complexity of quantum hardware. In this service-oriented paradigm, quantum circuits, which constitute high-value intellectual property, are exposed to risks of unauthorized access, reuse, and misuse. Digital watermarking has been explored as a promising mechanism for protecting quantum circuits by embedding ownership information for tracing and verification. However, driven by recent advances in generative artificial intelligence, the paradigm of quantum circuit design is shifting from individually and manually constructed circuits to automated synthesis based on quantum circuit generative models (QCGMs). In such generative settings, protecting only individual output circuits is insufficient, and existing post hoc, circuit-centric watermarking methods are not designed to integrate with the generative process, often failing to simultaneously ensure stealthiness, functional correctness, and robustness at scale. These limitations highlight ...
