Reverse-type Data Processing Inequality

November 29, 2024 Β· Declared Dead Β· πŸ› International Symposium on Information Theory

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Authors Paula Belzig, Li Gao, Graeme Smith, Peixue Wu arXiv ID 2411.19890 Category quant-ph: Quantum Computing Cross-listed cs.IT, math-ph Citations 6 Venue International Symposium on Information Theory Last Checked 5 months ago
Abstract
The quantum data processing inequality asserts that two quantum states become harder to distinguish when a noisy channel is applied. On the other hand, a reverse quantum data processing inequality characterizes whether distinguishability is preserved after the application of a noisy channel. In this work, we explore these concepts through contraction and expansion coefficients of the relative entropy of quantum channels. Our first result is that quantum channels with an input dimension greater than or equal to the output dimension do not have a non-zero expansion coefficient, which means that they cannot admit a reverse data-processing inequality. We propose a comparative approach by introducing a relative expansion coefficient, to assess how one channel expands relative entropy compared to another. We show that this relative expansion coefficient is positive for three important classes of quantum channels: depolarizing channels, generalized dephasing channels, and amplitude damping channels. As an application, we give the first rigorous construction of level-1 less noisy quantum channels that are non-degradable.
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