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The chain rule for the classical relative entropy ensures that the relative entropy between probability distributions on multipartite systems can be decomposed into a sum of relative entropies of suitably chosen conditional distributions on…

Quantum Physics · Physics 2020-03-18 Kun Fang , Omar Fawzi , Renato Renner , David Sutter

It is well established that the notion of min-entropy fails to satisfy the \emph{chain rule} of the form $H(X,Y) = H(X|Y)+H(Y)$, known for Shannon Entropy. Such a property would help to analyze how min-entropy is split among smaller blocks.…

Information Theory · Computer Science 2017-03-01 Maciej Skorski

The fidelity-based smooth min-relative entropy is a distinguishability measure that has appeared in a variety of contexts in prior work on quantum information, including resource theories like thermodynamics and coherence. Here we provide a…

Quantum Physics · Physics 2024-05-29 Theshani Nuradha , Mark M. Wilde

We introduce a novel generalization of entropy and conditional entropy from which most definitions from the literature can be derived as particular cases. Within this general framework, we investigate the problem of designing…

Information Theory · Computer Science 2018-11-27 MHR Khouzani , Pasquale Malacaria

This paper presents an enhanced post-quantum key agreement protocol based on R\'{e}nyi entropy, addressing vulnerabilities in the original construction while preserving information-theoretic security properties. We develop a theoretical…

Cryptography and Security · Computer Science 2026-03-10 Ruopengyu Xu , Chenglian Liu

For a state $\rho_{A_1^n B}$, we call a sequence of states $(\sigma_{A_1^k B}^{(k)})_{k=1}^n$ an approximation chain if for every $1 \leq k \leq n$, $\rho_{A_1^k B} \approx_\epsilon \sigma_{A_1^k B}^{(k)}$. In general, it is not possible to…

Quantum Physics · Physics 2024-02-12 Ashutosh Marwah , Frédéric Dupuis

In this work, maximal $\alpha$-leakage is introduced to quantify how much a quantum adversary can learn about any sensitive information of data upon observing its disturbed version via a quantum privacy mechanism. We first show that an…

Quantum Physics · Physics 2024-03-22 Bo-Yu Yang , Hsuan Yu , Hao-Chung Cheng

One-shot information theory entertains a plethora of entropic quantities, such as the smooth max-divergence, hypothesis testing divergence and information spectrum divergence, that characterize various operational tasks and are used to…

Quantum Physics · Physics 2020-08-24 Anurag Anshu , Mario Berta , Rahul Jain , Marco Tomamichel

The rates of quantum cryptographic protocols are usually expressed in terms of a conditional entropy minimized over a certain set of quantum states. In particular, in the device-independent setting, the minimization is over all the quantum…

Quantum Physics · Physics 2022-10-05 Peter Brown , Hamza Fawzi , Omar Fawzi

We investigate quantum R\'enyi entropic quantities, specifically those derived from 'sandwiched' divergence. This divergence is one of several proposed R\'enyi generalisations of the quantum relative entropy. We may define R\'enyi…

Quantum Physics · Physics 2021-10-04 Alexander McKinlay

Quantum information measures such as the entropy and the mutual information find applications in physics, e.g., as correlation measures. Generalizing such measures based on the R\'enyi entropies is expected to enhance their scope in…

Quantum Physics · Physics 2015-04-10 Mario Berta , Kaushik P. Seshadreesan , Mark M. Wilde

From the output produced by a memoryless deletion channel with a uniformly random input of known length $n$, one obtains a posterior distribution on the channel input. The difference between the Shannon entropy of this distribution and that…

Cryptography and Security · Computer Science 2020-03-27 Arash Atashpendar

The use of Mutual Information (MI) as a measure to evaluate the efficiency of cryptosystems has an extensive history. However, estimating MI between unknown random variables in a high-dimensional space is challenging. Recent advances in…

The aim of this paper is to investigate various information-theoretic measures, including entropy, mutual information, and some systematic measures that based on mutual information, for a class of structured spiking neuronal network. In…

Neurons and Cognition · Quantitative Biology 2019-12-04 Wenjie Li , Yao Li

Quantum information decoupling is a fundamental primitive in quantum information theory, underlying various applications in quantum physics. We prove a novel one-shot decoupling theorem formulated in terms of quantum relative entropy…

Quantum Physics · Physics 2026-02-20 Mario Berta , Hao-Chung Cheng , Yongsheng Yao

Mistrustful quantum cryptographic protocols encode information in incompatible observables, so that any attempt by a dishonest party to access multiple pieces of information necessarily involves a tradeoff. A natural class of such…

Quantum Physics · Physics 2026-03-31 Chen-Xun Weng , Minglong Qin , Yanglin Hu , Marco Tomamichel

Divergence chain rules for channels relate the divergence of a pair of channel inputs to the divergence of the corresponding channel outputs. An important special case of such a rule is the data-processing inequality, which tells us that if…

Quantum Physics · Physics 2024-05-21 Mario Berta , Marco Tomamichel

Most security proofs of quantum key distribution (QKD) assume that there is no unwanted information leakage about the state preparation process. However, this assumption is impossible to guarantee in practice, as QKD systems can leak…

Shannon's fundamental bound for perfect secrecy says that the entropy of the secret message cannot be larger than the entropy of the secret key initially shared by the sender and the legitimate receiver. Massey gave an information theoretic…

Information Theory · Computer Science 2016-11-17 Siu-Wai Ho , Terence H. Chan , Alex Grant , Chinthani Uduwerelle

Exponential models of distributions are widely used in machine learning for classiffication and modelling. It is well known that they can be interpreted as maximum entropy models under empirical expectation constraints. In this work, we…

Machine Learning · Computer Science 2012-07-19 Amir Globerson , Naftali Tishby