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In modern quantum information theory one deals with an idealized situation when the spacetime dependence of quantum phenomena is neglected. However the transmission and processing of (quantum) information is a physical process in spacetime.…

Quantum Physics · Physics 2016-09-08 Igor V. Volovich

Information theory establishes the fundamental limits on data transmission, storage, and processing. Quantum information theory unites information theoretic ideas with an accurate quantum-mechanical description of reality to give a more…

Quantum Physics · Physics 2017-02-01 Andrew W. Cross , Ke Li , Graeme Smith

Quantum information is about the entanglement of states. To this starting point we add parameters whereby a single state becomes a non-vanishing section of a bundle. We consider through examples the possible entanglement patterns of…

Quantum Physics · Physics 2023-11-23 M. H. Freedman , M. B. Hastings

In this review we integrate results of long term experimental study on ant "language" and intelligence which were fully based on fundamental ideas of Information Theory, such as the Shannon entropy, the Kolmogorov complexity, and the…

Information Theory · Computer Science 2015-05-14 Boris Ryabko , Zhanna Reznikova

Quantum information theory, particularly its entropic formulations, has made remarkable strides in characterizing quantum systems and tasks. However, a critical dimension remains underexplored: computational efficiency. While classical…

Quantum Physics · Physics 2026-05-05 Noam Avidan , Thomas A. Hahn , Joseph M. Renes , Rotem Arnon

In quantum Shannon theory, transmission of information is enhanced by quantum features. Up to very recently, the trajectories of transmission remained fully classical. Recently, a new paradigm was proposed by playing quantum tricks on two…

Computational Intelligence is a dead-end attempt to recreate human-like intelligence in a computing machine. The goal is unattainable because the means chosen for its accomplishment are mutually inconsistent and contradictory:…

Other Computer Science · Computer Science 2016-12-16 Emanuel Diamant

This paper begins with a discussion of integration over probability types (p-types). After doing that, the paper re-visits 3 mainstay problems of classical (non-quantum) Shannon Information Theory (SIT): source coding without distortion,…

Information Theory · Computer Science 2012-08-15 Robert R. Tucci

Semantic communication initiates a new direction for future communication. In this paper, we aim to establish a systematic framework of semantic information theory (SIT). First, we propose a semantic communication model and define the…

Information Theory · Computer Science 2024-01-26 Kai Niu , Ping Zhang

According to quantum mechanics, the informational content of isolated systems does not change in time. However, subadditivity of entropy seems to describe an excess of information when we look at single parts of a composite systems and…

Quantum Physics · Physics 2019-11-12 Marco Roncaglia

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

This monograph presents a unified treatment of single- and multi-user problems in Shannon's information theory where we depart from the requirement that the error probability decays asymptotically in the blocklength. Instead, the error…

Information Theory · Computer Science 2015-04-13 Vincent Y. F. Tan

Information theory is a practical and theoretical framework developed for the study of communication over noisy channels. Its probabilistic basis and capacity to relate statistical structure to function make it ideally suited for studying…

Neurons and Cognition · Quantitative Biology 2015-01-09 Simon R. Schultz , Robin A. A. Ince , Stefano Panzeri

Shannon's notion of relative information between two physical systems can function as foundation for statistical mechanics and quantum mechanics, without referring to subjectivism or idealism. It can also represent a key missing element in…

High Energy Physics - Theory · Physics 2016-01-21 Carlo Rovelli

There are (at least) three approaches to quantifying information. The first, algorithmic information or Kolmogorov complexity, takes events as strings and, given a universal Turing machine, quantifies the information content of a string as…

Information Theory · Computer Science 2011-11-29 David Balduzzi

The aim of this book is to develop "from the ground up" many of the major, exciting, pre- and post-millenium developments in the general area of study known as quantum Shannon theory. As such, we spend a significant amount of time on…

Quantum Physics · Physics 2026-01-06 Mark M. Wilde

Semantic communication has emerged as a promising paradigm to address the challenges of next-generation communication networks. While some progress has been made in its conceptualization, fundamental questions remain unresolved. In this…

Information Theory · Computer Science 2025-05-05 Javad Gholipour , Rafael F. Schaefer , Gerhard P. Fettweis

In quantum Shannon theory, the way information is encoded and decoded takes advantage of the laws of quantum mechanics, while the way communication channels are interlinked is assumed to be classical. In this Letter we relax the assumption…

Quantum Physics · Physics 2018-03-28 Daniel Ebler , Sina Salek , Giulio Chiribella

We compare the elementary theories of Shannon information and Kolmogorov complexity, the extent to which they have a common purpose, and where they are fundamentally different. We discuss and relate the basic notions of both theories:…

Information Theory · Computer Science 2020-07-21 Peter Grunwald , Paul Vitanyi

To infer information flow in any network of agents, it is important first and foremost to establish causal temporal relations between the nodes. Practical and automated methods that can infer causality are difficult to find, and the subject…

Neural and Evolutionary Computing · Computer Science 2024-12-11 Ali Tehrani-Saleh , Christoph Adami