Two-stage solution for ancilla-assisted quantum process tomography: error analysis and optimal design
Quantum process tomography (QPT) is a fundamental task to characterize the dynamics of quantum systems. In contrast to standard QPT, ancilla-assisted process tomography (AAPT) framework introduces an extra ancilla system such that a single input state is needed. In this paper, we extend the two-stag...
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Main Authors | , , , |
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Format | Journal Article |
Language | English |
Published |
31.10.2023
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Subjects | |
Online Access | Get full text |
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Summary: | Quantum process tomography (QPT) is a fundamental task to characterize the
dynamics of quantum systems. In contrast to standard QPT, ancilla-assisted
process tomography (AAPT) framework introduces an extra ancilla system such
that a single input state is needed. In this paper, we extend the two-stage
solution, a method originally designed for standard QPT, to perform AAPT. Our
algorithm has $O(Md_A^2d_B^2)$ computational complexity where $ M $ is the type
number of the measurement operators, $ d_A $ is the dimension of the quantum
system of interest, and $d_B$ is the dimension of the ancilla system. Then we
establish an error upper bound and further discuss the optimal design on the
input state in AAPT. A numerical example on a phase damping process
demonstrates the effectiveness of the optimal design and illustrates the
theoretical error analysis. |
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DOI: | 10.48550/arxiv.2310.20421 |