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We consider a line network of nodes, connected by additive white Gaussian noise channels, equipped with local feedback. We study the velocity at which information spreads over this network. For transmission of a data packet, we give an…

Information Theory · Computer Science 2024-10-28 Elad Domanovitz , Anatoly Khina , Tal Philosof , Yuval Kochman

Quantum communication leads to strong correlations, that can outperform classical ones. Complementary to previous works in this area, we investigate correlations in prepare-and-measure scenarios assuming a bound on the information content…

Information theory is an outstanding framework to measure uncertainty, dependence and relevance in data and systems. It has several desirable properties for real world applications: it naturally deals with multivariate data, it can handle…

Machine Learning · Statistics 2024-10-30 Valero Laparra , J. Emmanuel Johnson , Gustau Camps-Valls , Raul Santos-Rodríguez , Jesus Malo

The generalization error of a learning algorithm refers to the discrepancy between the loss of a learning algorithm on training data and that on unseen testing data. Various information-theoretic bounds on the generalization error have been…

Information Theory · Computer Science 2025-06-24 Xuetong Wu , Jonathan H. Manton , Uwe Aickelin , Jingge Zhu

Efforts to construct deeper, realistic, level of physical description, in which individual systems have, like in classical physics, preexisting properties revealed by measurements are known as hidden-variable programs. Demonstrations that a…

Quantum Physics · Physics 2009-09-15 Caslav Brukner , Marek Zukowski

Bell inequalities are important tools in contrasting classical and quantum behaviors. To date, most Bell inequalities are linear combinations of statistical correlations between remote parties. Nevertheless, finding the classical and…

Quantum Physics · Physics 2019-05-01 Amit Te'eni , Bar Y. Peled , Avishy Carmi , Eliahu Cohen

Basing on unified approach to {\it all} kinds of quantum capacities we show that the rate of quantum information transmission is bounded by the maximal attainable rate of coherent information. Moreover, we show that, if for any bipartite…

Quantum Physics · Physics 2009-11-06 Michal Horodecki , Pawel Horodecki , Ryszard Horodecki

The first part of this paper contains an introduction to Bell inequalities and Tsirelson's theorem for the non-specialist. The next part gives an explicit optimum construction for the "hard" part of Tsirelson's theorem. In the final part we…

Quantum Physics · Physics 2015-05-13 David Avis , Sonoko Moriyama , Masaki Owari

A measurement is deemed successful, if one can maximize the information gain by the measurement apparatus. Here, we ask if quantum coherence of the system imposes a limitation on the information gain during quantum measurement. First, we…

Quantum Physics · Physics 2020-04-02 Gautam Sharma , Sk Sazim , Arun Kumar Pati

Signal causality, the prohibition of superluminal information transmission, is the fundamental property shared by quantum measurement theory and relativity, and it is the key to understanding the connection between nonlocal measurement…

Quantum Physics · Physics 2011-07-05 Edward J. Gillis

The mutual information between two jointly distributed random variables $X$ and $Y$ is a functional of the joint distribution $P_{XY},$ which is sometimes difficult to handle or estimate. A coarser description of the statistical behavior of…

Information Theory · Computer Science 2016-11-17 Yanjun Han , Or Ordentlich , Ofer Shayevitz

The highest information rate at which quantum error-correction schemes work reliably on a channel, which is called the quantum capacity, is proven to be lower bounded by the limit of the quantity termed coherent information maximized over…

Quantum Physics · Physics 2007-05-23 Mitsuru Hamada

Incompatible, i.e. non-jointly measurable quantum measurements are a necessary resource for many information processing tasks. It is known that increasing the number of distinct measurements usually enhances the incompatibility of a…

Quantum Physics · Physics 2023-09-28 Lucas Tendick , Hermann Kampermann , Dagmar Bruß

We present a unifying picture of PAC-Bayesian and mutual information-based upper bounds on the generalization error of randomized learning algorithms. As we show, Tong Zhang's information exponential inequality (IEI) gives a general recipe…

Machine Learning · Computer Science 2021-10-26 Pradeep Kr. Banerjee , Guido Montúfar

Basic quantum information measures involved in the information analysis of quantum systems are considered. It is shown that the main quantum information measurement methods depend on whether the corresponding quantum events are compatible…

Quantum Physics · Physics 2007-05-23 B. A. Grishanin , V. N. Zadkov

One of the striking properties of quantum mechanics is the occurrence of the Bell-type non-locality. They are a fundamental feature of the theory that allows two parties that share an entangled quantum system to observe correlations…

We consider the information causality in the multi-receiver random access codes. Therein, no receiver can gain any information only from classical communication. We claim the following statement. Information causality still holds even with…

Quantum Physics · Physics 2013-05-30 Li-Yi Hsu

Pairwise Causal Discovery is the task of determining causal, anticausal, confounded or independence relationships from pairs of variables. Over the last few years, this challenging task has promoted not only the discovery of novel machine…

Machine Learning · Computer Science 2022-12-05 Felipe Giori , Flavio Figueiredo

We present a quantum information theory that allows for a consistent description of entanglement. It parallels classical (Shannon) information theory but is based entirely on density matrices (rather than probability distributions) for the…

Quantum Physics · Physics 2009-10-30 Nicolas J. Cerf , Chris Adami

Probabilities of Causation play a fundamental role in decision making in law, health care and public policy. Nevertheless, their point identification is challenging, requiring strong assumptions such as monotonicity. In the absence of such…

Machine Learning · Statistics 2023-04-06 Numair Sani , Atalanti A. Mastakouri , Dominik Janzing
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