Many Faces of Entropy or Bayesian Statistical Mechanics
Artikel i vetenskaplig tidskrift, 2010
Some 80-90 years ago, George A. Linhart, unlike A. Einstein, P. Debye, M. Planck and W. Nernst, managed to derive a very simple, but ultimately general mathematical formula for heat capacity versus temperature from fundamental thermodynamic principles, using what we would nowadays dub a "Bayesian approach to probability". Moreover, he successfully applied his result to fit the experimental data for diverse substances in their solid state over a rather broad temperature range. Nevertheless, Linhart's work was undeservedly forgotten, although it represents a valid and fresh standpoint on thermodynamics and statistical physics, which may have a significant implication for academic and applied science.Undeservedly forgotten: George A. Linhart's publications some 80-90 years ago in which-unlike Einstein, Debye, Planck and Nernst-he succeeded in deriving a simple, but ultimately general mathematical formula for heat capacity versus temperature from fundamental thermodynamic principles, using what we would nowadays dub a "Bayesian approach to probability", became totally forgotten, although they represent a valid and fresh standpoint on thermodynamics and statistical physics. The aim of this essay is to restore the memory of these great works
Statistical mechanics
Entropy
Heat capacity
Thermodynamics
Bayesian probability