Universal adjointation of isometry operations using conversion of quantum supermaps

Satoshi Yoshida1, Akihito Soeda2,3,1, and Mio Murao1,4

1Department of Physics, Graduate School of Science, The University of Tokyo, Hongo 7-3-1, Bunkyo-ku, Tokyo 113-0033, Japan
2Principles of Informatics Research Division, National Institute of Informatics, 2-1-2 Hitotsubashi, Chiyoda-ku, Tokyo 101-8430, Japan
3Department of Informatics, School of Multidisciplinary Sciences, SOKENDAI (The Graduate University for Advanced Studies), 2-1-2 Hitotsubashi, Chiyoda-ku, Tokyo 101-8430, Japan
4Trans-scale Quantum Science Institute, The University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan

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Abstract

Identification of possible transformations of quantum objects including quantum states and quantum operations is indispensable in developing quantum algorithms. Universal transformations, defined as input-independent transformations, appear in various quantum applications. Such is the case for universal transformations of unitary operations. However, extending these transformations to non-unitary operations is nontrivial and largely unresolved. Addressing this, we introduce $\textit{isometry adjointation}$ protocols that transform an input isometry operation into its adjoint operation, which include both unitary operation and quantum state transformations. The paper details the construction of parallel and sequential isometry adjointation protocols, derived from unitary inversion protocols using quantum combs and the (dual) Clebsch-Gordan transforms, and achieving optimal approximation error. This error is shown to be independent of the output dimension of the isometry operation. In particular, we explicitly obtain an asymptotically optimal parallel protocol achieving an approximation error $\epsilon = \Theta(d^2/n)$, where $d$ is the input dimension of the isometry operation and $n$ is the number of calls of the isometry operation. The research also extends to isometry inversion and universal error detection, employing semidefinite programming to assess optimal performances. The findings suggest that the optimal performance of general protocols in isometry adjointation and universal error detection is not dependent on the output dimension, and that indefinite causal order protocols offer advantages over sequential ones in isometry inversion and universal error detection.

Controlling and transforming quantum systems is essential for advancing quantum algorithms. One important goal is to develop universal transformations—protocols that work regardless of the specific input. This transformation has been explored for unitary operations, reversible operations preserving the size of the system. However, extending it to more general operations has remained a significant challenge. Isometry operations form an important class of quantum operations since they represent the encoding of quantum information to a larger system and can represent general quantum operations by embedding the output system into a larger system. Isometry operation is an information-preserving operation, but it is reversible only within a certain subspace since it spreads the input information to a larger system.

This work introduces new protocols to "undo" an unknown isometry operation. These protocols first check whether the input state lies within the invertible subspace (subspace check) and, if it does, apply the inverse operation (decoding)—all by transforming the original "do" operation without learning what it is. These protocols are designed to be highly accurate and efficient, regardless of the output dimension of the isometry operation, which can be much larger than the input dimension. This construction is based on a quantum circuit that converts the corresponding protocol for the unitary operation to handle the broader class of isometry operations.

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[4] Dmitry Grinko, Satoshi Yoshida, Mio Murao, and Maris Ozols, "Sequential quantum processes with group symmetries", arXiv:2510.07100, (2025).

[5] Satoshi Yoshida, Ryotaro Niwa, Takeru Utsumi, Ryuji Takagi, and Mio Murao, "Random dilation superchannel", arXiv:2512.21260, (2025).

[6] Robert Allen and Dominic Verdon, "Supermaps between channels of any type", arXiv:2410.01389, (2024).

[7] Zhenhuan Liu, Yunlong Xiao, and Zhenyu Cai, "Non-Markovian Noise Suppression Simplified through Channel Representation", arXiv:2412.11220, (2024).

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