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Query-optimal estimation of unitary channels in diamond distance

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

2023Year
21Citations
12Top-tier citations

Abstract

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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