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 new, simplified proof of the QAEP and therefore obtain a self-contained proof of the DPI for the von Neumann entropy
This thesis consolidates, improves and extends the smooth entropy framework for non-asymptotic infor...
© 2019 Author(s). One-shot information theory entertains a plethora of entropic quantities, such as ...
latex InfoStatPhys-unix.tex, 3 files, 2 figures, 32 pages http://www-spht.cea.fr/articles/T04/185Int...
The strength of quantum correlations is bounded from above by Tsirelson's bound. We establish a conn...
The quantum version of a fundamental entropic data-processing inequality is presented. It establishe...
The α-sandwiched Rényi divergence satisfies the data processing inequality, i.e. monotonicity under ...
Ahlswede R, Lober P. Quantum data processing. In: IEEE Transactions on Information Theory. IEEE TRA...
Abstract—This paper focuses on developing an alternative proof for an extremal entropy inequality, o...
This dissertation describes the progress made towards understanding several quantum entropies and th...
One of the predominant challenges when engineering future quantum information processors is that lar...
In most communication schemes, information is transmitted via travelling modes of electromagnetic ra...
Abstract—We provide a simple physical interpretation, in the context of the second law of thermodyna...
We provide a transparent, simple and unified treatment of recent results on the equality conditions ...
This book provides the reader with the mathematical framework required to fully explore the potentia...
In this paper, we generalize the notion of Shannon’s entropy power to the Rényi-entropy setting. Wit...
This thesis consolidates, improves and extends the smooth entropy framework for non-asymptotic infor...
© 2019 Author(s). One-shot information theory entertains a plethora of entropic quantities, such as ...
latex InfoStatPhys-unix.tex, 3 files, 2 figures, 32 pages http://www-spht.cea.fr/articles/T04/185Int...
The strength of quantum correlations is bounded from above by Tsirelson's bound. We establish a conn...
The quantum version of a fundamental entropic data-processing inequality is presented. It establishe...
The α-sandwiched Rényi divergence satisfies the data processing inequality, i.e. monotonicity under ...
Ahlswede R, Lober P. Quantum data processing. In: IEEE Transactions on Information Theory. IEEE TRA...
Abstract—This paper focuses on developing an alternative proof for an extremal entropy inequality, o...
This dissertation describes the progress made towards understanding several quantum entropies and th...
One of the predominant challenges when engineering future quantum information processors is that lar...
In most communication schemes, information is transmitted via travelling modes of electromagnetic ra...
Abstract—We provide a simple physical interpretation, in the context of the second law of thermodyna...
We provide a transparent, simple and unified treatment of recent results on the equality conditions ...
This book provides the reader with the mathematical framework required to fully explore the potentia...
In this paper, we generalize the notion of Shannon’s entropy power to the Rényi-entropy setting. Wit...
This thesis consolidates, improves and extends the smooth entropy framework for non-asymptotic infor...
© 2019 Author(s). One-shot information theory entertains a plethora of entropic quantities, such as ...
latex InfoStatPhys-unix.tex, 3 files, 2 figures, 32 pages http://www-spht.cea.fr/articles/T04/185Int...