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There are three ways to conceptualize entropy: entropy as an extensive thermodynamic quantity of physical systems (Clausius, Boltzmann, Gibbs), entropy as a measure for information production of ergodic sources (Shannon), and entropy as a…

Statistical Mechanics · Physics 2018-11-05 Stefan Thurner , Bernat Corominas-Murtra , Rudolf Hanel

A new axiomatic characterization with a minimum of conditions for entropy as a function on the set of states in quantum mechanics is presented. Traditionally unspoken assumptions are unveiled and replaced by proven consequences of the…

Mathematical Physics · Physics 2014-07-02 Bernhard Baumgartner

Shannon's information entropy measures of the uncertainty of an event's outcome. If learning about a system reflects a decrease in uncertainty, then a plausible intuition is that learning should be accompanied by a decrease in the entropy…

Robotics · Computer Science 2015-02-20 Paul E. Smaldino

The paper moves a step towards the full integration of statistical mechanics and information theory. Starting from the assumption that the thermodynamical system is composed by particles whose quantized energies can be modelled as…

Statistical Mechanics · Physics 2023-02-01 Arnaldo Spalvieri

Entropy has been a common index to quantify the complexity of time series in a variety of fields. Here, we introduce increment entropy to measure the complexity of time series in which each increment is mapped into a word of two letters,…

Data Analysis, Statistics and Probability · Physics 2016-01-20 Xiaofeng Liu , Aimin Jiang , Ning Xu , Jianru Xue

We propose a generalisation of Gibbs' statistical mechanics into the domain of non-negligible phase space correlations. Derived are the probability distribution and entropy as a generalised ensemble average, replacing…

Statistical Mechanics · Physics 2014-09-10 R. A. Treumann , W. Baumjohann

In this paper, some general properties of Shannon information measures are investigated over sets of probability distributions with restricted marginals. Certain optimization problems associated with these functionals are shown to be…

Information Theory · Computer Science 2020-08-13 Mladen Kovačević , Ivan Stanojević , Vojin Šenk

Information is a precise concept that can be defined mathematically, but its relationship to what we call "knowledge" is not always made clear. Furthermore, the concepts "entropy" and "information", while deeply related, are distinct and…

Adaptation and Self-Organizing Systems · Physics 2016-03-03 Christoph Adami

This article serves as a brief introduction to the Shannon information theory. Concepts of information, Shannon entropy and channel capacity are mainly covered. All these concepts are developed in a totally combinatorial flavor. Some issues…

Information Theory · Computer Science 2021-04-26 Ricky X. F. Chen

Sentence is a basic linguistic unit, however, little is known about how information content is distributed across different positions of a sentence. Based on authentic language data of English, the present study calculated the entropy and…

Computation and Language · Computer Science 2016-09-27 Shuiyuan Yu , Jin Cong , Junying Liang , Haitao Liu

The statistical mechanics of Gibbs is a juxtaposition of subjective, probabilistic ideas on the one hand and objective, mechanical ideas on the other. In this paper, we follow the path set out by Jaynes, including elements added…

Statistical Mechanics · Physics 2015-11-24 David M. Rogers , Thomas L. Beck , Susan B. Rempe

Shannon entropy ($S$), Fisher information ($I$) and a measure equivalent to Fisher-Shannon complexity $(C_{IS})$ of a ro-vibrational state of diatomic molecules (O$_2$, O$_2^+$, NO, NO$^+$) with generalized Kratzer potential is analyzed.…

Quantum Physics · Physics 2019-04-15 Sangita Majumdar , Neetik Mukherjee , Amlan K. Roy

The position- and momentum-space information entropies of the electron distributions of atomic clusters are calculated using a Woods-Saxon single particle potential. The same entropies are also calculated for nuclear distributions according…

Quantum Physics · Physics 2009-10-31 S. E. Massen , C. P. Panos

The Gibbs paradox is a conventional paradox in classical statistical mechanics, typically resolved by invoking quantum indistinguishability through the 1/N! correction. In this letter, we present a resolution within classical ensemble…

Statistical Mechanics · Physics 2026-02-09 Zheng Zhang

Shannon entropy and Fisher information functionals are known to quantify certain information-theoretic properties of continuous probability distributions of various origins. We carry out a systematic study of these functionals, while…

Quantum Physics · Physics 2007-05-23 Piotr Garbaczewski

In this paper we give an interpretation of Tsallis' nonextensive statistical mechanics based upon the information-theoretic point of view of Luzzi et al. [cond-mat/0306217; cond-mat/0306247; cond-mat/0307325], suggesting Tsallis' entropy to…

Statistical Mechanics · Physics 2015-06-24 F. Sattin

Complex systems that are characterized by strong correlations and fat-tailed distribution functions have been argued to be incompatible within the framework of Boltzmann-Gibbs entropy. As an alternative, so-called generalized entropies were…

Statistical Mechanics · Physics 2022-08-15 Rudolf Hanel , Stefan Thurner

We present estimators for entropy and other functions of a discrete probability distribution when the data is a finite sample drawn from that probability distribution. In particular, for the case when the probability distribution is a joint…

comp-gas · Physics 2008-02-03 David H. Wolpert , David R. Wolf

The electrical activity of external anal sphincter can be registered with surface electromyography. This signals are known to be highly complex and nonlinear. This work aims in characterisation of the information carried in the signals by…

Medical Physics · Physics 2018-12-31 Paulina Trybek , Michal Nowakowski , Jerzy Salowka , Lukasz Machura

The paper examines relationships between the conditional Shannon entropy and the expectation of $\ell_{\alpha}$-norm for joint probability distributions. More precisely, we investigate the tight bounds of the expectation of…

Information Theory · Computer Science 2020-08-24 Yuta Sakai , Ken-ichi Iwata
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