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- Marco Tomamichel, Masahito Hayashi
- IEEE Transactions on Information Theory
- 2013

We consider two fundamental tasks in quantum information theory, data compression with quantum side information, as well as randomness extraction against quantum side information. We characterize these tasks for general sources using so-called one-shot entropies. These characterizations-in contrast to earlier results-enable us to derive tight second-order… (More)

The Rényi entropies constitute a family of information measures that generalizes the well-known Shannon entropy, inheriting many of its properties. They appear in the form of unconditional and conditional entropies, relative entropies or mutual information, and have found many applications in information theory and beyond. Various generalizations of Rényi… (More)

The Rényi entropies constitute a family of information measures that generalizes the well-known Shannon entropy, inheriting many of its properties. They appear in the form of unconditional and conditional entropies, relative entropies or mutual information, and have found many applications in information theory and beyond. Various generalizations of Rényi… (More)

- Marco Tomamichel, Roger Colbeck, Renato Renner
- IEEE Transactions on Information Theory
- 2010

In classical and quantum information theory, operational quantities such as the amount of randomness that can be extracted from a given source or the amount of space needed to store given data are normally characterized by one of two entropy measures, called smooth min-entropy and smooth max-entropy, respectively. While both entropies are equal to the von… (More)

- Marco Tomamichel, Roger Colbeck, Renato Renner
- IEEE Transactions on Information Theory
- 2009

The classical asymptotic equipartition property is the statement that, in the limit of a large number of identical repetitions of a random experiment, the output sequence is virtually certain to come from the typical set, each member of which is almost equally likely. In this paper, a fully quantum generalization of this property is shown, where both the… (More)

- Marco Tomamichel, Charles Ci Wen Lim, Nicolas Gisin, Renato Renner
- Nature communications
- 2012

Despite enormous theoretical and experimental progress in quantum cryptography, the security of most current implementations of quantum key distribution is still not rigorously established. One significant problem is that the security of the final key strongly depends on the number, M, of signals exchanged between the legitimate parties. Yet, existing… (More)

- Marco Tomamichel, Vincent Yan Fu Tan
- IEEE Transactions on Information Theory
- 2013

This paper shows that the logarithm of the ε-error capacity (average error probability) for n uses of a discrete memoryless channel (DMC) is upper bounded by the normal approximation plus a third-order term that does not exceed [ 1/ 2] logn +O(1) if the ε-dispersion of the channel is positive. This matches a lower bound by Y. Polyanskiy (2010)… (More)

- Marco Tomamichel
- ArXiv
- 2015

Acknowledgements I was introduced to quantum information theory during my PhD studies in Renato Renner's group at ETH Zurich. It is from him that I learned most of what I know about quantum cryptography and smooth entropies. Renato also got me interested more generally in finite resource information theory as well as the entropies and other information… (More)

- Marco Tomamichel, Vincent Yan Fu Tan
- IEEE Transactions on Information Theory
- 2014

We study the performance limits of state-dependent discrete memoryless channels with a discrete state available at both the encoder and the decoder. We establish the ε-capacity as well as necessary and sufficient conditions for the strong converse property for such channels when the sequence of channel states is not necessarily stationary,… (More)

- Vincent Yan Fu Tan, Marco Tomamichel
- IEEE Transactions on Information Theory
- 2014

This paper shows that, under the average error probability formalism, the third-order term in the normal approximation for the additive white Gaussian noise channel with a maximal or equal power constraint is at least (1/2) log n + O(1). This improves on the lower bound by Polyanskiy-Poor-Verdú (2010) and matches the upper bound proved by the same… (More)