Kolmogorov equations (Markov jump process)
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In the context of a continuous-time Markov process, the Kolmogorov equations, including Kolmogorov forward equations and Kolmogorov backward equations, are a pair of systems of differential equations that describe the time-evolution of the probability , where (the state space) and are the final and initial time respectively.
For the case of denumerable state space we put in place of . Kolmogorov forward equations read
while Kolmogorov backward equations are
The functions are continuous and differentiable in both time arguments. They represent the probability that the system that was in state at time jumps to state at some later time . The continuous quantities satisfy
The original derivation of the equations by Kolmogorov  starts with the Chapman-Kolmogorov equation (Kolmogorov called it Fundamental equation) for time-continuous and differentiable Markov processes on a finite, discrete state space. In this formulation, it is assumed that the probabilities are continuous and differentiable functions of . Also adequate limit properties for the derivatives are assumed. Feller  derives the equations under slightly different conditions, starting with the concept of purely discontinuous Markov process and formulating them for more general state spaces. Feller  proves the existence of solutions of probabilistic character to the Kolmogorov forward equations and Kolmogorov backward equations under natural conditions.
Relation with the generating function
Still in the discrete state case, letting and assuming that the system initially is found in state , The Kolmogorov forward equations describe an initial value problem for finding the probabilities of the process, given the quantities . We put and
For the case of a pure death process with constant rates the only nonzero coefficients are . Letting
A brief historical note can be found at Kolmogorov equations
- Continuous-time Markov process
- Master equation
- Fokker–Planck equation
- Kolmogorov backward equations (diffusion)
- Kolmogoroff, A. (1931). "�ber die analytischen Methoden in der Wahrscheinlichkeitsrechnung". Mathematische Annalen 104: 415–458. doi:10.1007/BF01457949.
- Feller, Willy (1940) "On the Integro-Differential Equations of Purely Discontinuous Markoff Processes", Transactions of the American Mathematical Society, 48 (3), 488-515 JSTOR 1990095
- Bailey, Norman T.J. (1990) The Elements of Stochastic Processes with Applications to the Natural Sciences, Wiley. ISBN 0-471-52368-2 (page 90)