Process tomography for Clifford unitaries

We present an algorithm for performing quantum process tomography on an unknown $n$-qubit unitary $C$ from the Clifford group. Our algorithm uses Bell basis measurements to deterministically learn $C$ with $4n + 3$ queries, which is the asymptotically optimal query complexity. In contrast to previous algorithms that required access to $C^\dagger$ to achieve optimal query complexity, our algorithm achieves the same performance without querying $C^\dagger$. Additionally, we show the algorithm is robust to perturbations and can efficiently learn the closest Clifford to an unknown non-Clifford unitary $U$ using query overhead that is logarithmic in the number of qubits.

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Publication Details

Journal
Physical review. A/Physical review, A
Published
2025-12-02
DOI
https://doi.org/10.1103/zjfb-3jzb
Primary Topic
Quantum Computing Algorithms and Architecture
Type
article
Field-Weighted Citation Impact
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article

Process tomography for Clifford unitaries

Karl J. Friston
Physical review. A/Physical review, A
Quantum Computing Algorithms and Architecture
article

Process tomography for Clifford unitaries

Karl J. Friston
article en

Abstract

We present an algorithm for performing quantum process tomography on an unknown $n$-qubit unitary $C$ from the Clifford group. Our algorithm uses Bell basis measurements to deterministically learn $C$ with $4n + 3$ queries, which is the asymptotically optimal query complexity. In contrast to previous algorithms that required access to $C^\dagger$ to achieve optimal query complexity, our algorithm achieves the same performance without querying $C^\dagger$. Additionally, we show the algorithm is robust to perturbations and can efficiently learn the closest Clifford to an unknown non-Clifford unitary $U$ using query overhead that is logarithmic in the number of qubits.

Physical review. A/Physical review, AVol. 113(1)
Cornell University (US)
Openalex Percentile: Top 79%
Quantum Computing Algorithms and Architecture
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