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Related papers: Information Entropy, Information Distances and Com…

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Entropy and information can be considered dual: entropy is a measure of the subspace defined by the information constraining the given ambient space. Negative entropies, arising in na\"ive extensions of the definition of entropy from…

Probability · Mathematics 2023-03-06 Daniel Lazarev

The present work studies aspects of the electronic correlation in confined H$^{-}$, He and Li$^+$ atoms in their ground states using the informational entropies. In this way, different variational wavefunctions are employed in order of…

Atomic Physics · Physics 2021-06-10 Wallas S. Nascimento , Marcos M. de Almeida , Frederico V. Prudente

Shannon entropy, a cornerstone of information theory, statistical physics and inference methods, is uniquely identified by the Shannon-Khinchin or Shore-Johnson axioms. Generalizations of Shannon entropy, motivated by the study of…

Data Analysis, Statistics and Probability · Physics 2026-04-20 Andrea Somazzi , Diego Garlaschelli

By extrapolating the energies of non-relativistic atoms and their ions with up to 3000 electrons within Kohn-Sham density functional theory, we find that the ionization potential remains finite and increases across a row, even as…

Materials Science · Physics 2015-05-19 Lucian A. Constantin , John C. Snyder , John P. Perdew , Kieron Burke

The Shannon entropy, the desequilibrium and their generalizations (R\'enyi and Tsallis entropies) of the three-dimensional single-particle systems in a spherically-symmetric potential $V(r)$ can be decomposed into angular and radial parts.…

Quantum Physics · Physics 2017-01-17 J. S. Dehesa , I. V. Toranzo , D. Puertas-Centeno

We survey and introduce concepts and tools located at the intersection of information theory and network biology. We show that Shannon's information entropy, compressibility and algorithmic complexity quantify different local and global…

Molecular Networks · Quantitative Biology 2015-12-14 Hector Zenil , Narsis A. Kiani , Jesper Tegnér

We report measurements of the spin susceptibility and the electron effective mass for two-dimensional electrons confined at the interfaces of MgxZn1-xO/ZnO single heterostructures (x = 0.05, 0.08, and 0.11), grown by molecular-beam epitaxy…

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 compute the isotope shifts of the \emph{total} electron binding energy of neutral atoms and singly charged ions up to element $Z=120$, using relativistic Hartree-Fock method including the Breit interaction. Field shift coefficients are…

Atomic Physics · Physics 2025-07-30 V. A. Dzuba , V. V. Flambaum

We calculate the phonon density of states (DOS) for strongly amorphous materials with a short-ranged interatomic potential. Exponentially decaying and abruptly truncated interatomic potentials are examined. Thermally excited mean square…

Materials Science · Physics 2015-03-13 D. J. Priour

Shannon information entropy is a natural measure of probability (de)localization and thus (un)predictability in various procedures of data analysis for model systems. We pay particular attention to links between the Shannon entropy and the…

Statistical Mechanics · Physics 2007-05-23 Piotr Garbaczewski

The quantification of the complexity of networks is, today, a fundamental problem in the physics of complex systems. A possible roadmap to solve the problem is via extending key concepts of information theory to networks. In this paper we…

Disordered Systems and Neural Networks · Physics 2015-05-13 Kartik Anand , Ginestra Bianconi

Entropic uncertainty relations are interesting in their own rights as well as for a lot of applications. Keeping this in mind, we try to make the corresponding inequalities as tight as possible. The use of parametrized entropies also allows…

Quantum Physics · Physics 2023-05-30 Alexey E. Rastegin

Upper and lower bounds are obtained for the joint entropy of a collection of random variables in terms of an arbitrary collection of subset joint entropies. These inequalities generalize Shannon's chain rule for entropy as well as…

Information Theory · Computer Science 2024-05-07 Mokshay Madiman , Prasad Tetali

We define correlational (von Neumann) entropy for an individual quantum state of a system whose time-independent hamiltonian contains random parameters and is treated as a member of a statistical ensemble. This entropy is representation…

chao-dyn · Physics 2013-01-16 Valentin V. Sokolov , B. Alex Brown , Vladimir Zelevinsky

We argue certain nonviolent local quantum field theory (LQFT) modification considered at the global horizon ($r=2M$) of a static spherically-symmetric black hole can lead to adiabatic leakage of quantum information in the form of Hawking…

General Relativity and Quantum Cosmology · Physics 2017-07-07 Alexander Y. Yosifov , Lachezar G. Filipov

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

We present certain universal bounds on the capacity of quantum information storage and on the time scale of its retrieval for a generic quantum field theoretic system. The capacity, quantified by the microstate entropy, is bounded from…

High Energy Physics - Theory · Physics 2022-01-12 Gia Dvali

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 rapid scaling of artificial intelligence models has revealed a fundamental tension between model capacity (storage) and inference efficiency (computation). While classical information theory focuses on transmission and storage limits,…

Information Theory · Computer Science 2026-01-01 Jianfeng Xu , Zeyan Li