Tensorization of the strong data processing inequality for quantum chi-square divergences

04/13/2019

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by   Yu Cao, et al.

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Quantifying the contraction of classical and quantum states under noisy channels is an important topic in the information theory. Among various techniques, the strong data processing inequality, as a refinement of the well-known data processing inequality, has lately received much attention for classical noisy channels. In this work, we apply the strong data processing inequality to study quantum noisy channels and under certain assumptions, we prove the tensorization of the strong data processing inequality for a family of quantum chi-square divergences. In addition, we discuss the connection between the quantum strong data processing inequality constant and the quantum maximal correlation.