C
Constantino Tsallis
Researcher at National Institute of Standards and Technology
Publications - 362
Citations - 27533
Constantino Tsallis is an academic researcher from National Institute of Standards and Technology. The author has contributed to research in topics: Statistical mechanics & Entropy (statistical thermodynamics). The author has an hindex of 61, co-authored 337 publications receiving 24535 citations. Previous affiliations of Constantino Tsallis include Massachusetts Institute of Technology & National Council for Scientific and Technological Development.
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Journal ArticleDOI
Possible generalization of Boltzmann-Gibbs statistics
TL;DR: In this paper, a generalized form of entropy was proposed for the Boltzmann-Gibbs statistics with the q→1 limit, and the main properties associated with this entropy were established, particularly those corresponding to the microcanonical and canonical ensembles.
Book
Introduction to Nonextensive Statistical Mechanics
TL;DR: In this article, the Boltzmann-Gibbs Statistical Mechanics (BSM) theory is generalized to nonextensive statistical mechanics and applied in thermodynamic and non-thermodynamic applications.
Journal ArticleDOI
The role of constraints within generalized nonextensive statistics
TL;DR: In this paper, the Gibbs-Jaynes path for introducing statistical mechanics is based on the adoption of a specific entropic form S and of physically appropriate constraints, and the consequences of some special choices for (iii) and their formal and practical implications for the various physical systems that have been studied in the literature are analyzed.
Book ChapterDOI
Entropy
TL;DR: The concept of entropy constitutes, together with energy, a cornerstone of contemporary physics and related areas as discussed by the authors , and it was originally introduced by Clausius in 1865 along abstract lines focusing on thermodynamical irreversibility of macroscopic physical processes.
Book
Nonextensive Entropy: Interdisciplinary Applications
TL;DR: A great variety of complex phenomena in many scientific fields exhibit power-law behavior, reflecting a hierarchical or fractal structure as mentioned in this paper, and these phenomena seem to be susceptible to description using approaches drawn from thermodynamics or statistical mechanics, particularly approaches involving the maximization of entropy and of Boltzmann-Gibbs statistical mechanics.