Matrix analysis
Elements of information theory
Elements of information theory
Quantum computation and quantum information
Quantum computation and quantum information
Min- and max-relative entropies and a new entanglement monotone
IEEE Transactions on Information Theory
The operational meaning of min- and max-entropy
IEEE Transactions on Information Theory
A fully quantum asymptotic equipartition property
IEEE Transactions on Information Theory
Duality between smooth min- and max-entropies
IEEE Transactions on Information Theory
A simple proof of the strong subadditivity inequality
Quantum Information & Computation
Cryptographic distinguishability measures for quantum-mechanical states
IEEE Transactions on Information Theory
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The data processing inequality (DPI) is a fundamental feature of information theory. Informally it states that you cannot increase the information content of a quantum system by acting on it with a local physical operation. When the smooth min-entropy is used as the relevant information measure, then the DPI follows immediately from the definition of the entropy. The DPI for the von Neumann entropy is then obtained by specializing the DPI for the smooth min-entropy by using the quantum asymptotic equipartition property (QAEP). We provide a short proof of the QAEP and therefore obtain a self-contained proof of the DPI for the von Neumann entropy.