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Comment published on 6 March 2019, see Entropy 2019, 21(3), 251.
Open AccessArticle

Entropy, Shannon’s Measure of Information and Boltzmann’s H-Theorem

Department of Physical Chemistry, The Hebrew University of Jerusalem, Jerusalem 91904, Israel
Academic Editors: Geert Verdoolaege and Kevin H. Knuth
Entropy 2017, 19(2), 48; https://doi.org/10.3390/e19020048
Received: 23 November 2016 / Revised: 17 January 2017 / Accepted: 21 January 2017 / Published: 24 January 2017
(This article belongs to the Special Issue Selected Papers from MaxEnt 2016)
We start with a clear distinction between Shannon’s Measure of Information (SMI) and the Thermodynamic Entropy. The first is defined on any probability distribution; and therefore it is a very general concept. On the other hand Entropy is defined on a very special set of distributions. Next we show that the Shannon Measure of Information (SMI) provides a solid and quantitative basis for the interpretation of the thermodynamic entropy. The entropy measures the uncertainty in the distribution of the locations and momenta of all the particles; as well as two corrections due to the uncertainty principle and the indistinguishability of the particles. Finally we show that the H-function as defined by Boltzmann is an SMI but not entropy. Therefore; much of what has been written on the H-theorem is irrelevant to entropy and the Second Law of Thermodynamics. View Full-Text
Keywords: entropy; Shannon’s measure of information; Second Law of Thermodynamics; H-theorem entropy; Shannon’s measure of information; Second Law of Thermodynamics; H-theorem
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Ben-Naim, A. Entropy, Shannon’s Measure of Information and Boltzmann’s H-Theorem. Entropy 2017, 19, 48.

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