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An information theory description of finite systems explicitly evolving in time is presented. We impose a MaxEnt variational principle on the Shannon entropy at a given time while the constraints are set at a former time. The resulting…

Nuclear Theory · Physics 2008-11-26 F. Gulminelli , Ph. Chomaz , O. Juillet , M. J. Ison , C. O. Dorso

The primary objective of quantum Shannon theory is to evaluate the capacity of quantum channels. In spite of the existence of rigorous coding theorems that quantify the transmission of information through quantum channels, superadditivity…

Quantum Physics · Physics 2024-01-17 Rajiuddin Sk , Prasanta K. Panigrahi

Shannon's theory of information was built on the assumption that the information carriers were classical systems. Its quantum counterpart, quantum Shannon theory, explores the new possibilities arising when the information carriers are…

Quantum Physics · Physics 2019-05-30 Giulio Chiribella , Hlér Kristjánsson

We consider linear time-varying channels with additive white Gaussian noise. For a large class of such channels we derive rigorous estimates of the eigenvalues of the correlation matrix of the effective channel in terms of the sampled…

Information Theory · Computer Science 2016-11-17 Brendan Farrell , Thomas Strohmer

This paper strengthens the interpretation and understanding of the classical capacity of the pure-loss bosonic channel, first established in [Giovannetti et al., Physical Review Letters 92, 027902 (2004), arXiv:quant-ph/0308012]. In…

Quantum Physics · Physics 2014-07-22 Mark M. Wilde , Andreas Winter

The mutual information is bounded from above by a decreasing affine function of the square of the distance between the input distribution and the set of all capacity-achieving input distributions $\Pi_{\mathcal{A}}$, on small enough…

Information Theory · Computer Science 2025-04-24 Barış Nakiboğlu , Hao-Chung Cheng

The amount of information transmissible through a communications channel is determined by the noise characteristics of the channel and by the quantities of available transmission resources. In classical information theory, the amount of…

Quantum Physics · Physics 2009-11-10 Mikio Fujiwara , Masahiro Takeoka , Jun Mizuno , Masahide Sasaki

With the advent of massive data outputs at a regular rate, admittedly, signal processing technology plays an increasingly key role. Nowadays, signals are not merely restricted to physical sources, they have been extended to digital sources…

Information Theory · Computer Science 2015-07-28 Yi Lu

Shannon's metric of "Entropy" of information is a foundational concept of information theory. This article is a primer for novices that presents an intuitive way of understanding, remembering, and/or reconstructing Shannon's Entropy metric…

Information Theory · Computer Science 2014-05-09 Sriram Vajapeyam

We consider the discrete-time intersymbol interference (ISI) channel model, with additive Gaussian noise and fixed i.i.d. inputs. In this setting, we investigate the expression put forth by Shamai and Laroia as a conjectured lower bound for…

Information Theory · Computer Science 2014-01-08 Yair Carmon , Shlomo Shamai

Information Causality is a physical principle which states that the amount of randomly accessible data over a classical communication channel cannot exceed its capacity, even if the sender and the receiver have access to a source of…

Quantum Physics · Physics 2021-06-09 Nikolai Miklin , Marcin Pawłowski

Traditional channel capacity based on the discrete spatial dimensions mismatches the continuous electromagnetic fields. For the wireless communication system in a limited region, the spatial discretization may results in information loss…

Information Theory · Computer Science 2023-02-21 Zhongzhichao Wan , Jieao Zhu , Zijian Zhang , Linglong Dai , Chan-Byoung Chae

With the aid of a toy model, the Monty Hall Problem (MHP), the counterintuitive and theoretically problematic concept of negative information in classical systems is well understood. It is shown that, as its quantum counterpart, classical…

Information Theory · Computer Science 2020-03-04 Alvaro Lopez-Medrano

This article introduces the physics of information in the context of molecular biology and genomics. Entropy and information, the two central concepts of Shannon's theory of information and communication, are often confused with each other…

Biomolecules · Quantitative Biology 2007-05-23 Christoph Adami

In this paper, we attempt to derive the expression of ensemble average internal energy in long-range interaction complex system. Further, the Shannon entropy hypothesis is used to derive the probability distribution function of energy. It…

Statistical Mechanics · Physics 2019-02-04 Yanxiu Liu , Shenglei Zhang , Liu He , Cheng Xu , Zhifu Huang

Entropy or information is a fundamental quantity contained in a system in statistical mechanics and information theory. In this paper, a definition of classical information entropy of parton distribution functions is suggested. The…

High Energy Physics - Phenomenology · Physics 2024-05-28 Rong Wang

In information theory, one major goal is to find useful functions that summarize the amount of information contained in the interaction of several random variables. Specifically, one can ask how the classical Shannon entropy, mutual…

Information Theory · Computer Science 2025-02-14 Leon Lang , Pierre Baudot , Rick Quax , Patrick Forré

The most natural way to describe an information-carrying system containing a specific noise is an additive white Gaussian-noise (AWGN) channel. In bosonic quantum systems (especially the Gaussian case), although the classical information…

Quantum Physics · Physics 2019-05-14 Kabgyun Jeong , Hun Hee Lee , Youngrong Lim

The statistical properties of physical systems in thermal equilibrium are blatantly different from their far-from-equilibrium counterparts. In the latter, fluctuations often dominate the dynamics and might cluster in ordered patterns in the…

Understanding a complex system entails capturing the non-trivial collective phenomena that arise from interactions between its different parts. Information theory is a flexible and robust framework to study such behaviours, with several…

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