Understanding the Factor 2 in the Langevin Stochastic Differential Equation

In summary, the conversation discusses the Langevin stochastic differential equation and its relation to Brownian motion. The equation includes a factor of 2 in the expression for <f(t)f(t')>, which may seem unnecessary but is included in the definition to account for the connection to the Fokker-Planck equation. The recommended book on the topic is Kurt Jacob's "Stochastic Processes in Physics and Chemistry."
  • #1
Niles
1,866
0
Hi

I am reading about the Langevin stochastic differential equation
[tex]
\frac{d}{dt}p = -\alpha p + f(t)
[/tex]
where p is the momentum and f(t) the Langevin force. By definition <F(t)>=0 and <f(t)f(t')> = 2Dg(t-t'), where g is the second order correlation function.

My question is, why is there a factor 2 in the expression for <f(t)f(t')>? I can't seem to find an answer in any book, but they all write the factor.

I would be glad to receive some feedback.


Niles.
 
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  • #2
There are two phenomenological ways of describing simple Brownian motion.

One is with something called a Fokker-Planck equation http://www.pma.caltech.edu/~mcc/Ph127/b/Lecture17.pdf . In the definition of the Fokker-Planck equation there is a quantity called the diffusion constant D.

The other is with the Langevin equation. You are right that there is no need to start off with the "2" in the definition of the Langevin equation. Let's say you start off "g" instead. You will find that you can derive a Fokker-Planck equation from the Langevin equation where g=2D, with the g coming from the Langevin, and the D from the Fokker-Planck. Since they knew that, they just used 2D in the initial definition. See http://web.phys.ntnu.no/~ingves/Teaching/TFY4275/Downloads/kap6.pdf Eq 6.3, 6.8, 6.27 and 6.35.
 
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  • #3
Thanks, that is very kind of you. These things are really interesting. I need to find a good book on this topic, uptil now I have just been using the web.

Best.
Niles.
 
  • #5
Thanks, I just checked my library, and they have it. I'll pick it up Monday.
 

What is the meaning of Factor 2 in the Langevin Stochastic Differential Equation?

The Factor 2 in the Langevin Stochastic Differential Equation represents the rate of change of the random variable in the equation. It is also known as the diffusion coefficient and determines the strength of the random fluctuations in the system.

How does the Factor 2 affect the behavior of the system?

The value of Factor 2 has a direct impact on the diffusion process in the system. A higher value of Factor 2 leads to a faster diffusion process, resulting in a more random and unpredictable behavior of the system. On the other hand, a lower value of Factor 2 results in a slower diffusion process, leading to a more stable and predictable behavior of the system.

What are the units of Factor 2 in the Langevin Stochastic Differential Equation?

The units of Factor 2 in the Langevin Stochastic Differential Equation depend on the specific system being studied. However, it is typically measured in units of time squared, such as seconds squared or minutes squared.

How is Factor 2 related to the other parameters in the Langevin Stochastic Differential Equation?

Factor 2 is related to the other parameters in the Langevin Stochastic Differential Equation through the fluctuation-dissipation theorem. This theorem states that the strength of the random fluctuations (Factor 2) is proportional to the dissipation coefficient (a measure of energy loss) and the temperature of the system.

What is the significance of Factor 2 in the Langevin Stochastic Differential Equation in real-world applications?

Factor 2 plays a crucial role in understanding the behavior of many physical and biological systems, such as Brownian motion, diffusion processes, and chemical reactions. It is also used in various fields, including physics, chemistry, biology, and finance, to model and analyze complex systems and their dynamics.

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