The Kolmogorov backward equation (KBE) (diffusion) and its adjoint sometimes known as the Kolmogorov forward equation (diffusion) are partial differential equations (PDE) that arise in the theory of continuous-time continuous-state Markov processes. Both were published by Andrey Kolmogorov in 1931.[1] Later it was realized that the forward equation was already known to physicists under the name Fokker - Planck equation; the KBE on the other hand was new.
pt(x)
s>t
pt(x)
pt(x)
The Kolmogorov backward equation on the other hand is useful when we are interested at time t in whether at a future time s the system will be in a given subset of states B, sometimes called the target set. The target is described by a given function
us(x)
us(x)=1B
t, (t<s)
us(x)
Assume that the system state
Xt
dXt=\mu(Xt,t)dt+\sigma(Xt,t)dWt,
then the Kolmogorov backward equation is[2]
\partial | p(x,t)=\mu(x,t) | |
\partialt |
\partial | |
\partialx |
p(x,t)+
1 | |
2 |
| ||||
\sigma |
p(x,t),
for
t\les
p(x,s)=us(x)
p(x,t)
dt
This equation can also be derived from the Feynman–Kac formula by noting that the hit probability is the same as the expected value of
us(x)
x
t
\Pr(Xs\inB\midXt=x)=E[us(x)\midXt=x].
Historically, the KBE was developed before the Feynman–Kac formula (1949).
With the same notation as before, the corresponding Kolmogorov forward equation is
\partial | p(x,s)=- | |
\partials |
\partial | |
\partialx |
[\mu(x,s)p(x,s)]+
1 | |
2 |
\partial2 | |
\partialx2 |
[\sigma2(x,s)p(x,s)],
for
s\get
p(x,t)=pt(x)