Polynomial transformations of data encoded in quantum operations are a building block of quantum algorithms, and their query complexity measures how often those operations are used. For multiple variables, existing methods either realize restricted polynomial families or implement monomials separately at a query cost e...
Ming-Rui Jing, Xin Wang, Zhan Yu et al.· 0 citations
Formal verification is becoming increasingly practical for quantum computing, yet the ability of AI agents to construct machine-checkable proofs in this domain remains unmeasured. We introduce Lean-QuantumAlg-Bench and Lean-QIT-Bench, two Lean 4 benchmarks containing 36 and 40 theorem-completion tasks for quantum algor...
Lei Zhang, Yusheng Zhao, Yimeng Cao et al.· 1 citation· ⚡1
The formalization develops the mathematical foundations for analyzing quantum attacks in two cryptographic settings: a 2048-bit modulus in the RSA-2048 and the standardized elliptic curve over a 256-bit prime field (P-256).
Lei Zhang, Yusheng Zhao, Hongshun Yao et al.· 2 citations
Lean-QIT provides a machine-readable foundation for formal QIT and a compositional knowledge substrate for emerging AI-assisted formalization, automated proof search, and agentic reasoning in quantum information and computation.
This work formalizes major components of QNN theory in a connected lean 4 development checked by a proof kernel, expecting this work to provide a machine-checkable foundation for QNN theory and a step toward AI-assisted or automated design of quantum machine learning algorithms.
M. Jing, Lei Zhang, Yusheng Zhao et al.· 2 citations
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