Derivation of the differential Chapman-Kolmogorov Equation

In summary, the integral equation represents the probability density of a Markov process taking a certain value at a certain time given its value at a previous time. To derive the differential CK equation, the time derivative is taken and the resulting operator is defined in terms of a density. However, the functional form of the operator may differ depending on how the variables are defined.
  • #1
vancouver_water
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TL;DR Summary
I am following the book "The Theory of Open Quantum Systems" by Breuer and Petruccione. I can follow the derivation of the integral CK equation but do not understand their derivation of the differential CK equation.
The integral equation is [tex]T(x_3,t_3|x_1,t_1)=\int \text{d}x_2T(x_3,t_3|x_2,t_2)T(x_2,t_2|x_1,t_1) [/tex] where [itex]T(x_3,t_3|x_1,t_1)[/itex] is the probability density of a Markov process taking the value [itex]x_3[/itex] at time [itex]t_3[/itex] given that it took the value of [itex]x_1[/itex] at time [itex]t_1[/itex]. So far so good. To derive the differential CK equation, they take the time derivative of the integral equation and the result is [tex]\frac{\partial}{\partial t}T(x,t|x',t')=A(t)T(x,t|x',t')[/tex] where [itex]A(t)[/itex] is time translation linear operator defined in terms of a density as [tex]A(t)\rho(x)=\lim_{\Delta t\rightarrow 0}\frac{1}{\Delta t}\int \text{d}x'[T(x,t+\Delta t|x',t)-\delta(x-x')]\rho(x').[/tex] I don't understand how to derive that form of [itex]A(t)[/itex]. What I would think (since they are differentiating w.r.t. the first time parameter) is that
[tex]\begin{align*}
\frac{\partial}{\partial t_3}T(x_3,t_3|x_1,t_1) &= \lim_{\Delta t\rightarrow 0}\frac{1}{\Delta t}\int \text{d}x_2[T(x_3,t_3+\Delta t|x_2,t_2)T(x_2,t_2|x_1,t_1)-T(x_3,t_3|x_2,t_2)T(x_2,t_2|x_1,t_1)] \\ &= \lim_{\Delta t\rightarrow 0}\frac{1}{\Delta t}\int \text{d}x_2[T(x_3,t_3+\Delta t|x_2,t_2)-T(x_3,t_3|x_2,t_2)]T(x_2,t_2|x_1,t_1)]
\end{align*}[/tex]
but I cannot get this into the same functional form as what they get. They only have one time parameter in their [itex]A(t)[/itex] but I still have all three time parameters.

What am I missing?

Thanks!
 
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  • #2
vancouver_water said:
They only have one time parameter in their [itex]A(t)[/itex] but I still have all three time parameters.

On https://www.sciencedirect.com/topics/mathematics/chapman-kolmogorov-equation the article "The Master Equation" gives equation 1.5 as a "simplified form" of the CK equation. It's actually a different equation since the variables are defined differently. Perhaps the book you are reading uses such an interpretation.
 

1. What is the differential Chapman-Kolmogorov equation?

The differential Chapman-Kolmogorov equation is a mathematical equation used to describe the evolution of a stochastic process. It is commonly used in the field of probability theory and is named after mathematicians Sydney Chapman and Andrey Kolmogorov.

2. What is the significance of the Chapman-Kolmogorov equation?

The Chapman-Kolmogorov equation is significant because it allows for the calculation of the probability of a stochastic process at a future time, given its current state. This makes it a valuable tool in predicting the behavior of complex systems and is widely used in fields such as physics, finance, and engineering.

3. How is the differential Chapman-Kolmogorov equation derived?

The differential Chapman-Kolmogorov equation is derived using the Kolmogorov forward equation, which describes the evolution of a probability distribution over time. By taking the limit of this equation as the time interval approaches zero, we arrive at the differential Chapman-Kolmogorov equation.

4. What are the assumptions made in the derivation of the Chapman-Kolmogorov equation?

The derivation of the Chapman-Kolmogorov equation assumes that the stochastic process is Markovian, meaning that its future behavior is only dependent on its current state and not on its past history. It also assumes that the process is continuous and has a finite state space.

5. How is the Chapman-Kolmogorov equation used in practical applications?

The Chapman-Kolmogorov equation is used in practical applications to model and predict the behavior of complex systems, such as stock prices, weather patterns, and population dynamics. It is also used in the development of statistical models and algorithms for data analysis and prediction.

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