Kramers–Moyal expansion
In stochastic processes, Kramers–Moyal expansion refers to a Taylor series expansion of the master equation, named after Hans Kramers and José Enrique Moyal.[1][2] This expansion transforms the integro-differential master equation
where (for brevity, this probability is denoted by ) is the transition probability density, to an infinite order partial differential equation[3][4][5]
where
Here is the transition probability rate. Fokker–Planck equation is obtained by keeping only the first two terms of the series in which is the drift and is the diffusion coefficient.
Pawula theorem
The Pawula theorem states that the expansion either stops after the first term or the second term[6][7]. If the expansion continues past the second term it must contain an infinite number of terms, in order that the solution to the equation be interpretable as a probability density function.[8]
Implementations
- Implementation in Python: https://github.com/LRydin/KramersMoyal [9]
References
- Kramers, H. A. (1940). "Brownian motion in a field of force and the diffusion model of chemical reactions". Physica. 7 (4): 284–304. doi:10.1016/S0031-8914(40)90098-2.
- Moyal, J. E. (1949). "Stochastic processes and statistical physics". Journal of the Royal Statistical Society. Series B (Methodological). 11 (2): 150–210. JSTOR 2984076.
- Gardiner, C. (2009). Stochastic Methods (4th ed.). Berlin: Springer. ISBN 978-3-642-08962-6.
- Van Kampen, N. G. (1992). Stochastic Processes in Physics and Chemistry. Elsevier. ISBN 0-444-89349-0.
- Risken, H. (1996). "Fokker–Planck equation". The Fokker–Planck Equation. Berlin, Heidelberg: Springer. pp. 63–95. ISBN 3-540-61530-X.
- R. F. Pawula, "Generalizations and extensions of the Fokker- Planck-Kolmogorov equations," in IEEE Transactions on Information Theory, vol. 13, no. 1, pp. 33-41, January 1967, doi: 10.1109/TIT.1967.1053955.
- Pawula, R. F. (1967). Approximation of the linear Boltzmann equation by the Fokker-Planck equation. Physical review, 162(1), 186.
- Risken, Hannes. "The Fokker-Planck Equation: Methods of Solution and Applications".
- Rydin Gorjão, L.; Meirinhos, F. (2019). "kramersmoyal: Kramers--Moyal coefficients for stochastic processes". Journal of Open Source Software. 4 (44): 1693. doi:10.21105/joss.01693.