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Distributed systems, such as biological and artificial neural networks, process information via complex interactions engaging multiple subsystems, resulting in high-order patterns with distinct properties across scales. Investigating how…

Information Theory · Computer Science 2025-04-23 Aaron J. Gutknecht , Fernando E. Rosas , David A. Ehrlich , Abdullah Makkeh , Pedro A. M. Mediano , Michael Wibral

We prove a variety of new and refined uniform continuity bounds for entropies of both classical random variables on an infinite state space and of quantum states of infinite-dimensional systems. We obtain the first tight continuity estimate…

Quantum Physics · Physics 2024-11-20 Simon Becker , Nilanjana Datta , Michael G. Jabbour

A survey is given summarizing the state of the art of describing information processing in Quantum Decision Theory, which has been recently advanced as a novel variant of decision making, based on the mathematical theory of separable…

Physics and Society · Physics 2015-05-13 V. I. Yukalov , D. Sornette

We deploy Shannon's information entropy to the distribution of branching fractions in a particle decay. This serves to quantify how important a given new reported decay channel is, from the point of view of the information that it adds to…

We study the time evolution of the excess value of capacity of entanglement between a locally excited state and ground state in free, massless fermionic theory and free Yang-Mills theory in four spacetime dimensions. Capacity has…

High Energy Physics - Theory · Physics 2021-07-07 Pratik Nandy

The study of mutual entropy (information) and capacity in classica l system was extensively done after Shannon by several authors like Kolmogor ov and Gelfand. In quantum systems, there have been several definitions of t he mutual entropy…

Quantum Physics · Physics 2007-05-23 Masanori Ohya

Researchers have proposed formal definitions of quantitative information flow based on information theoretic notions such as the Shannon entropy, the min entropy, the guessing entropy, belief, and channel capacity. This paper investigates…

Cryptography and Security · Computer Science 2011-12-20 Hirotoshi Yasuoka , Tachio Terauchi

We discuss the capacity of quantum channels for information transmission and storage. Quantum channels have dual uses: they can be used to transmit known quantum states which code for classical information, and they can be used in a purely…

Quantum Physics · Physics 2008-12-18 C. Adami , N. J. Cerf

We study how the Shannon entropy of sequences produced by an information source converges to the source's entropy rate. We synthesize several phenomenological approaches to applying information theoretic measures of randomness and memory to…

Statistical Mechanics · Physics 2007-05-23 James P. Crutchfield , David P. Feldman

This paper proposes a novel entropy encoding technique for lossless data compression. Representing a message string by its lexicographic index in the permutations of its symbols results in a compressed version matching Shannon entropy of…

Information Theory · Computer Science 2017-03-24 Abu Bakar Siddique

Like a silver thread, quantum entanglement [1] runs through the foundations and breakthrough applications of quantum information theory. It cannot arise from local operations and classical communication (LOCC) and therefore represents a…

Researchers have proposed formal definitions of quantitative information flow based on information theoretic notions such as the Shannon entropy, the min entropy, the guessing entropy, and channel capacity. This paper investigates the…

Cryptography and Security · Computer Science 2010-04-02 Hirotoshi Yasuoka , Tachio Terauchi

Despite the growing popularity of deep learning technologies, high memory requirements and power consumption are essentially limiting their application in mobile and IoT areas. While binary convolutional networks can alleviate these…

Computer Vision and Pattern Recognition · Computer Science 2020-08-05 Dmitry Ignatov , Andrey Ignatov

In this paper, we present a new multi-scale information content calculation method based on Shannon information (and Shannon entropy). The original method described by Claude E. Shannon and based on the logarithm of the probability of…

Information Theory · Computer Science 2023-05-23 Zsolt Pocze

We prove the existence of (one-way) communication tasks with a subconstant versus superconstant asymptotic gap, which we call "doubly infinite," between their quantum information and communication complexities. We do so by studying the…

Quantum Physics · Physics 2016-05-09 Zi-Wen Liu , Christopher Perry , Yechao Zhu , Dax Enshan Koh , Scott Aaronson

We propose a new thermodynamic, relativistic relationship between information and entropy, which is closely analogous to the classic Maxwell electro-magnetic equations. Determination of whether information resides in points of…

General Physics · Physics 2007-05-23 Michael C. Parker , Stuart D. Walker

An information-theoretic framework is introduced to analyze last-layer embedding, focusing on learned representations for regression tasks. We define representation-rate and derive limits on the reliability with which input-output…

Information Theory · Computer Science 2026-05-27 Deborah Pereg , Michael Wand

Informational contributions to thermodynamics can be studied in isolation by considering systems with fully-degenerate Hamiltonians. In this regime, being in non-equilibrium -- termed informational non-equilibrium -- provides thermodynamic…

Quantum Physics · Physics 2025-05-15 Chung-Yun Hsieh , Benjamin Stratton , Hao-Cheng Weng , Valerio Scarani

Entropy notions for $\varepsilon$-incremental practical stability and incremental stability of deterministic nonlinear systems under disturbances are introduced. The entropy notions are constructed via a set of points in state space which…

Optimization and Control · Mathematics 2022-09-13 Michelle S. Chong

Information capacity enhancement through the coherent control of channels has attracted much attention of late, with work exploring the effect of coherent control of channel causal orders, channel superpositions, and information encoding.…

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