For every quantum channel, the identification capacity is at most the entanglement-assisted transmission capacity, with equality for low-noise channels and strict inequality for a family of transpose-depolarizing channels.
Quantum Channel Simulation and the Channel's Smooth Max-Information
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abstract
We study the general framework of quantum channel simulation, that is, the ability of a quantum channel to simulate another one using different classes of codes. First, we show that the minimum error of simulation and the one-shot quantum simulation cost under no-signalling assisted codes are given by semidefinite programs. Second, we introduce the channel's smooth max-information, which can be seen as a one-shot generalization of the mutual information of a quantum channel. We provide an exact operational interpretation of the channel's smooth max-information as the one-shot quantum simulation cost under no-signalling assisted codes, which significantly simplifies the study of channel simulation and provides insights and bounds for the case under entanglement-assisted codes. Third, we derive the asymptotic equipartition property of the channel's smooth max-information; i.e., it converges to the quantum mutual information of the channel in the independent and identically distributed asymptotic limit. This implies the quantum reverse Shannon theorem in the presence of no-signalling correlations. Finally, we explore the simulation cost of various quantum channels.
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quant-ph 1years
2026 1verdicts
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The entanglement-assisted transmission capacity is a strong converse bound for identification
For every quantum channel, the identification capacity is at most the entanglement-assisted transmission capacity, with equality for low-noise channels and strict inequality for a family of transpose-depolarizing channels.