Many Faces of Entropy or Bayesian Statistical Mechanics

Journal article, 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