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In this paper, we characterize the saturation of four universal inequalities in quantum information theory, including a variant version of strong subadditivity inequality for von Neumann entropy, the coherent information inequality, the…

Quantum Physics · Physics 2015-04-22 Lin Zhang , Junde Wu , Shao-Ming Fei

The Shannon entropy of a random variable $X$ has much behaviour analogous to a signed measure. Previous work has concretized this connection by defining a signed measure $\mu$ on an abstract information space $\tilde{X}$, which is taken to…

Information Theory · Computer Science 2023-05-15 Keenan J. A. Down , Pedro A. M. Mediano

The coherent information concept is used to analyze a variety of simple quantum systems. Coherent information was calculated for the information decay in a two-level atom in the presence of an external resonant field, for the information…

Quantum Physics · Physics 2009-10-31 B. A. Grishanin , V. N. Zadkov

Mutual information is the reciprocal information that is common to or shared by two or more parties. Quantum mutual information for bipartite quantum systems is non-negative, and bears the interpretation of total correlation between the two…

Quantum Physics · Physics 2017-08-02 Asutosh Kumar

Word embeddings provide point representations of words containing useful semantic information. We introduce multimodal word distributions formed from Gaussian mixtures, for multiple word meanings, entailment, and rich uncertainty…

Machine Learning · Statistics 2019-09-10 Ben Athiwaratkun , Andrew Gordon Wilson

Distributed representations of words encode lexical semantic information, but what type of information is encoded and how? Focusing on the skip-gram with negative-sampling method, we found that the squared norm of static word embedding…

Computation and Language · Computer Science 2023-11-03 Momose Oyama , Sho Yokoi , Hidetoshi Shimodaira

A model of quantum noisy channel with input encoding by a classical random vector is described. An equation of optimality is derived to determine a complete set of wave functions describing quantum decodings based on quasi-measurements…

Quantum Physics · Physics 2007-05-23 V. P. Belavkin , R. L. Stratonovich

Quantum mutual information (QMI) not only displays the mutual information in the system but also demonstrates some quantum correlation beyond entanglement. We explore here the two alternatives of multipartite quantum mutual information…

Quantum Physics · Physics 2023-09-01 Yu Guo , Lizhong Huang

We use mutual information as a measure of the entanglement between 'physical' and thermo-field double degrees of freedom in field theories at finite temperature. We compute this "thermo-mutual information" in simple toy models: a quantum…

High Energy Physics - Theory · Physics 2016-03-22 Ian A. Morrison , Matthew M. Roberts

This study revisits label smoothing via a form of information bottleneck. Under the assumption of sufficient model flexibility and no conflicting labels for the same input, we theoretically and experimentally demonstrate that the model…

Machine Learning · Computer Science 2025-08-21 Sota Kudo

Shannon's mutual information of a random multiple antenna and multipath channel is studied in the general case where the channel impulse response is an ergodic and stationary process which is assumed to be available at the receiver. From…

Information Theory · Computer Science 2019-05-09 Walid Hachem , Adrien Hardy , Shlomo Shamai

We discuss averaged turbulence modeling of multi-scales of length for an incompressible Newtonian fluid, with the help of the maximum information principle. We suppose that there exists a function basis to decompose the turbulent…

Fluid Dynamics · Physics 2010-09-10 L. Tao , M. Ramakrishna

We prove that the average smooth Renyi entropy rate will approach the entropy rate of a stationary, ergodic information source, which is equal to the Shannon entropy rate for a classical information source and the von Neumann entropy rate…

Quantum Physics · Physics 2018-02-13 Berry Schoenmakers , Jilles Tjoelker , Pim Tuyls , Evgeny Verbitskiy

In this paper, we introduce new Stein identities for gamma target distribution as well as a new non-linear channel specifically designed for gamma inputs. From these two ingredients, we derive an explicit and simple formula for the…

Probability · Mathematics 2019-08-20 Benjamin Arras , Yvik Swan

The task of compressing classical information in the one-shot scenario is studied in the setting where the decompressor additionally has access to some given quantum side information. In this hybrid classical-quantum version of the famous…

Quantum Physics · Physics 2012-03-27 Joseph M. Renes , Renato Renner

This paper proposes the estimation of a mutual shape from a set of different segmentation results using both active contours and information theory. The mutual shape is here defined as a consensus shape estimated from a set of different…

Image and Video Processing · Electrical Eng. & Systems 2021-02-18 S. Jehan-Besson , R. Clouard , C. Tilmant , A. de Cesare , A. Lalande , J. Lebenberg , P. Clarysse , L. Sarry , F. Frouin , M. Garreau

Mutual information has many applications in image alignment and matching, mainly due to its ability to measure the statistical dependence between two images, even if the two images are from different modalities (e.g., CT and MRI). It…

Computer Vision and Pattern Recognition · Computer Science 2024-07-11 Jiecheng Liao , Junhao Lu , Jeff Ji , Jiacheng He

In this article we provide, from a novel perspective, arguments that support the idea that, in the wake of Cox' approach to probability theory, von Neumann's entropy should be the natural one in Quantum Mechanics. We also generalize the…

Quantum Physics · Physics 2015-10-02 F. Holik , A. Plastino , M. Sáenz

We extend the data compression theorem to the case of ergodic quantum information sources. Moreover, we provide an asymptotically optimal compression scheme which is based on the concept of high probability subspaces. The rate of this…

Quantum Physics · Physics 2007-05-23 Igor Bjelakovic , Arleta Szkola

We derive the closed-form expression of the maximum mutual information - the maximum value of $I(X;Z)$ obtainable via training - for a broad family of neural network architectures. The quantity is essential to several branches of machine…

Machine Learning · Computer Science 2020-06-12 Brandon Foggo , Nanpeng Yu
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