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
Deterministic exact inversion of an arbitrary $d$-dimensional unitary requires {$\Theta(d^2)$} coherent forward calls in the worst case. We ask how this cost changes for Hamiltonian evolution $U(x)=\exp(i\sum_j x_jH_j)$ when the generators are known but the parameters are hidden. For one-parameter families with a fixed...
Ji-Zhe Lai, M. Jing, Erdong Huang et al.· 0 citations
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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