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Complementarity relations between various characterizations of a probability distribution are at the core of information theory. In particular, lower and upper bounds for the entropic function are of great importance. In applied topics, we…

Quantum Physics · Physics 2022-09-07 Alexey E. Rastegin

In this article we discuss the formal structure of a generalized information theory based on the extension of the probability calculus of Kolmogorov to a (possibly) non-commutative setting. By studying this framework, we argue that quantum…

Quantum Physics · Physics 2016-01-19 F. Holik , G. M. Bosyk , G. Bellomo

It is well known that a Shannon based definition of information entropy leads in the classical case to the Boltzmann entropy. It is tempting to regard the Von Neumann entropy as the corresponding quantum mechanical definition. But the…

Quantum Physics · Physics 2009-11-10 Alexander Stotland , Andrei A. Pomeransky , Eitan Bachmat , Doron Cohen

As conventional communication systems based on classic information theory have closely approached the limits of Shannon channel capacity, semantic communication has been recognized as a key enabling technology for the further improvement of…

Information Theory · Computer Science 2023-06-06 Jiancheng Tang , Qianqian Yang , Zhaoyang Zhang

Information theory provides a mathematical foundation to measure uncertainty in belief. Belief is represented by a probability distribution that captures our understanding of an outcome's plausibility. Information measures based on…

Information Theory · Computer Science 2020-01-17 Jed A. Duersch , Thomas A. Catanach

Accurately determining dependency structure is critical to discovering a system's causal organization. We recently showed that the transfer entropy fails in a key aspect of this---measuring information flow---due to its conflation of dyadic…

Information Theory · Computer Science 2017-11-22 Ryan G. James , James P. Crutchfield

Despite the wide usage of information as a concept in science, we have yet to develop a clear & concise scientific definition. This paper is aimed at laying the foundations for a new theory concerning the mechanics of information alongside…

General Physics · Physics 2017-07-13 Kiyam Lin , SongLing Lin

In this paper we construct a theory of quantum mechanics based on Shannon information theory. We define a few principles regarding information-based frames of reference, including explicitly the concept of information covariance, and show…

General Physics · Physics 2011-05-25 Joakim Munkhammar

In this research article, we use the Shannon's formalism to investigate the quantum information entropy of a particle trapped by the Aharonov-Bohm-type effect. For quantum information study, it is necessary to investigate the eigenstates of…

Quantum Physics · Physics 2023-05-31 F. C. E. Lima , A. R. P. Moreira , C. A. S. Almeida , C. O. Edet , N. Ali

We survey the prospects for an Information Dynamics which can serve as the basis for a fundamental theory of information, incorporating qualitative and structural as well as quantitative aspects. We motivate our discussion with some basic…

Logic in Computer Science · Computer Science 2016-04-12 Samson Abramsky

Quantum mechanics, information theory, and relativity theory are the basic foundations of theoretical physics. The acquisition of information from a quantum system is the interface of classical and quantum physics. Essential tools for its…

Quantum Physics · Physics 2011-04-29 Asher Peres , Daniel R. Terno

Integrated Information Theory is one of the leading models of consciousness. It aims to describe both the quality and quantity of the conscious experience of a physical system, such as the brain, in a particular state. In this contribution,…

Neurons and Cognition · Quantitative Biology 2020-02-19 Johannes Kleiner , Sean Tull

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…

Information complexity is the interactive analogue of Shannon's classical information theory. In recent years this field has emerged as a powerful tool for proving strong communication lower bounds, and for addressing some of the major open…

Computational Complexity · Computer Science 2015-04-28 Omri Weinstein

In this paper we formalize the notions of information elements and information lattices, first proposed by Shannon. Exploiting this formalization, we identify a comprehensive parallelism between information lattices and subgroup lattices.…

Information Theory · Computer Science 2007-10-08 Hua Li , Edwin K. P. Chong

Kolmogorov argued that the concept of information exists also in problems with no underlying stochastic model (as Shannon's information representation) for instance, the information contained in an algorithm or in the genome. He introduced…

Discrete Mathematics · Computer Science 2008-07-01 Joel Ratsaby

According to E.T. Jaynes and E.P. Wigner, entropy is an anthropomorphic concept in the sense that in a physical system correspond many thermodynamic systems. The physical system can be examined from many points of view each time examining…

Information Theory · Computer Science 2015-12-03 Panteleimon Rodis

Statements of Shannon's Noiseless Coding Theorem by various authors, including the original, are reviewed and clarified. Traditional statements of the theorem are often unclear as to when it applies. A new notation is introduced and the…

Information Theory · Computer Science 2010-11-01 L. F. Johnson

We pedagogically present the information theory as originally established, explaining its essential ideas and paying attention to the expression employed to measure the amount of information. Also we discussed relationships between…

Quantum Physics · Physics 2019-12-10 Wallas S. Nascimento , Marcos M. de Almeida , Frederico V. Prudente

This paper introduces several fundamental concepts in information theory from the perspective of their origins in engineering. Understanding such concepts is important in neuroscience for two reasons. Simply applying formulae from…

Information Theory · Computer Science 2016-03-29 Mark D. McDonnell , Shiro Ikeda , Jonathan H. Manton