 By definition, a probability density \(\varrho\) is stationary if it does not change over time. Given that observable quantities are associated with phase averages and that equilibrium is defined in terms of the constancy of the macroscopic parameters characterising the system, it is natural to regard the stationarity of the distribution as a necessary condition for equilibrium because stationary distributions yield constant averages. For this reason Gibbs refers to stationarity as the ‘condition of statistical equilibrium’.