Continuity equation for probability as a requirement of inference over paths

Abstract

In this work we present the fundamental ideas of inference over paths, and show how this formalism implies the continuity equation, which is central for the derivation of the main partial differential equations that constitute non-equilibrium statistical mechanics. Equations such as the Liouville equation, Fokker-Planck equation, among others can be recovered as particular cases of the continuity equation, under different probability fluxes. We derive the continuity equation in its most general form through what we call the \bf time-slicing equation, which lays down the procedure to go from the representation in terms of a path probability functional $\rho[X()]$ to a time-dependent probability density $\rho(x; t)$. The original probability functional $\rho[X()]$ can in principle be constructed from different methods of inference; in this work we sketch an application using the maximum path entropy or maximum caliber principle.