Posted

Aadil Oufkir, Filippo Girardi (Jan 08 2026).
Abstract: We prove that learning an unknown quantum channel with input dimension dAd_A, output dimension dBd_B, and Choi rank rr to diamond distance ε\varepsilon requires Ω ⁣(dAdBrεlog(dBr/ε)) \Omega\!\left( \frac{d_A d_B r}{\varepsilon \log(d_B r / \varepsilon)} \right) queries. This improves the best previous Ω(dAdBr)\Omega(d_A d_B r) bound by introducing explicit ε\varepsilon-dependence, with a scaling in ε\varepsilon that is near-optimal when dA=rdBd_A=rd_B but not tight in general. The proof constructs an ensemble of channels that are well-separated in diamond norm yet admit Stinespring isometries that are close in operator norm.

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