Entropy and Its Applications across Disciplines

Dear Colleagues,

The entropy concept was born initially in thermodynamics and is credited to the work of Rudolf Clausius. It was successively interpreted in terms of probability/statistics by Ludwig Boltzmann and J. Willard Gibbs, and ultimately led to the formulation of equilibrium statistical mechanics. The principle of maximum entropy (MaxEnt) allows an elegant derivation of the various statistical ensembles as emphasized by Jaynes by using the information entropy introduced by Shannon.

Entropy and the MaxEnt principle are now commonly used in many disciplines for the analysis of both complex equilibrium and non-equilibrium systems and is being increasingly employed in a variety of contexts, such as ecology, spectral analysis, electron microscopy, and neuroscience for inference from incomplete data. In all these applications, one is faced with problems related to the level of description of the system or coarse graining, which interestingly influence the final results.

This Special Issue invites contributions from leading groups to present original results or review the state-of-the-art of the use of entropy or the MaxEnt principle in their individual disciplines. This will lead to a cross-fertilization of ideas and techniques, and illuminate the use of these powerful techniques across disciplines.

Prof. Dr. Amos Maritan
Dr. Samir Suweis
Dr. Jordi Hidalgo
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Entropy is an international peer-reviewed open access monthly journal published by MDPI.

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