Quantum Information Processing with Finite Resources - Mathematical Foundations
By Marco Tomamichel. arXiv.org, 2015
339 citations recorded by the source corpus.
This book provides the reader with the mathematical framework required to fully explore the potential of small quantum information processing devices. As decoherence will continue to limit their size, it is essential to master the conceptual tools which make such investigations possible. A strong emphasis is given to information measures that are essential for the study of devices of finite size, including Rnyi entropies and smooth entropies. The presentation is self-contained and includes rigorous and concise proofs of the most important properties of these measures. The first chapters will introduce the formalism of quantum mechanics, with particular emphasis on norms and metrics for quantum states. This is necessary to explore quantum generalizations of Rnyi divergence and conditional entropy, information measures that lie at the core of information theory. The smooth entropy framework is discussed next and provides a natural means to lift many arguments from information theory to the quantum setting. Finally selected applications of the theory to statistics and cryptography are discussed. The book is aimed at graduate students in Physics and Information Theory. Mathematical fluency is necessary, but no prior knowledge of quantum theory is required.
Subfields: Artificial Intelligence
View Paper: https://www.semanticscholar.org/paper/892ce8a350dcd06718b30532a72f558b5d5534ce
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In Artificial Intelligence
Citations in the corpus
- A Tight Uniform Continuity Bound for Equivocation (2019, background): “Various forms of conditional Rényi entropies share this invariance [18], [19].”