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FOCS2023顶会

Query-optimal estimation of unitary channels in diamond distance

Jeongwan Haah, Robin Kothari, Ryan O'Donnell, Ewin Tang

2023年份
21被引次数
12顶会引用

摘要

We consider process tomography for unitary quantum channels. Given access to an unknown unitary channel acting on a d-dimensional qudit, we aim to output a classical description of a unitary that is ε\varepsilon-close to the unknown unitary in diamond norm. We design an algorithm achieving error ε\varepsilon using O( d2/ε)O\left(\mathrm{~d}^{2} / \varepsilon\right) applications of the unknown channel and only one qudit. This improves over prior results, which use O( d3/ε2)O\left(\mathrm{~d}^{3} / \varepsilon^{2}\right) [via standard process tomography] or O( d2.5/ε)O\left(\mathrm{~d}^{2.5} / \varepsilon\right) [Yang, Renner, and Chiribella, PRL 2020] applications. To show this result, we introduce a simple technique to “bootstrap” an algorithm that can produce constant-error estimates to one that can produce ε\varepsilon-error estimates with the Heisenberg scaling. Finally, we prove a complementary lower bound showing that estimation requires Ω(d2/ε)\Omega\left(\mathrm{d}^{2} / \varepsilon\right) applications, even with access to the inverse or controlled versions of the unknown unitary. This shows that our algorithm has both optimal query complexity and optimal space complexity.

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