How and why does statistical mechanics work
Navinder Singh

TL;DR
This paper reviews the foundations of statistical mechanics, arguing that ergodicity is not essential for equilibrium, emphasizing the role of macroscopic observables, large degrees of freedom, and critiques of various interpretations including chaos and Bayesian perspectives.
Contribution
It challenges the traditional emphasis on ergodicity, highlighting the importance of macroscopic observables and large system size, and critically examines different philosophical and quantum approaches.
Findings
Ergodicity is not relevant for equilibrium statistical mechanics.
Large degrees of freedom and properties of macroscopic observables explain the success of statistical mechanics.
Critiques of ergodic and Bayesian interpretations of statistical mechanics.
Abstract
As the title says we want to answer the question; how and why does statistical mechanics work? As we know from the most used prescription of Gibbs we calculate the phase space averages of dynamical quantities and we find that these phase averages agree very well with experiments. Clearly actual experiments are not done on a hypothetical ensemble they are done on the actual system in the laboratory and these experiments take a finite amount of time. Thus it is usually argued that actual measurements are time averages and they are equal to phase averages due to ergodicity. Aim of the present review is to show that ergodicity is not relevant for equilibrium statistical mechanics (with Tolman and Landau). We will see that the solution of the problem is in the very peculiar nature of the macroscopic observables and with the very large number of the degrees of freedom involved in macroscopic…
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Taxonomy
TopicsQuantum many-body systems · Advanced Thermodynamics and Statistical Mechanics · Statistical Mechanics and Entropy
