Fokker Planck Solution Biased Random Walk

In summary, the Fokker Planck relation for a biased random walk is derived in part a) of the assignment question. In part b), the solution to the differential equation for P(x,t) is obtained by defining a new frame of reference y=x-vt and rewriting the partial derivatives in terms of the new variable. The lecturer uses the chain rule to expand the derivative with respect to time, where y is not considered constant and x is held constant. This helps simplify the equation and solve for P(x,t).
  • #1
beth92
16
0
This is part b) of an assignment question. In part a) we were asked to derive the Fokker Planck relation for the biased random walk. The answer is:

dP/dt = -vdP/dx + D d2P/dx2

Where the first term is the drift term due to the biased motion and the second term is the diffusion term.

Then in part b) we were asked to solve this differential equation for P(x,t). I already have the written out solution to this question however I don't understand one of the steps the lecturer has taken.
First of all we define a new frame of reference y=x-vt in an attempt to get rid of the drift term (as we will then simply have the non-biased fokker-planck relation which we can solve). We then set out to rewrite the partial derivatives from the above equation in terms of the new variable y. Here the lecturer's solution emphasises that when deriving with respect to time, y is not a constant (y=y(t)) and x is considered constant. He writes the following:

dP(y,t)/dt |x=const=dP(y,t)/dt|y=x-vt

=dP(y,t)/dt + dy/dt * dP(y,t)/dy

I'm not sure why he has taken that last step - where have the two terms come from? It seems to me like he is adding the derivative twice (as the second term in the last line is just the dP/dt term again expanded using the chain rule).

If anyone can explain why he's done it this way then I will understand the rest of the question okay.

Thanks!
 
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  • #2
It's just the chain rule:
[tex]\frac{d}{dt} f(y(t), z(t)) = \frac{\partial f}{\partial y} \frac{dy}{dt}+\frac{\partial f}{\partial z} \frac{dz}{dt}[/tex]

Where your function has the form [itex]P = P(y(t), t)[/itex] <-- has two t dependent terms
To make this clearer let y(t) just as is and put z(t)=t, So that your [itex]P(y(t), z(t))[/itex],
So by the chain rule
[tex]\frac{d}{dt} P(y(t), z(t)) = \frac{\partial P}{\partial y} \frac{dy}{dt}+\frac{\partial P}{\partial z} \frac{dz}{dt}[/tex]
but remember [itex]z[/itex] was just [itex]t[/itex], so [itex]dz/dt=1[/itex] and you get
[tex]\frac{d}{dt} P(y(t), z(t)) = \frac{\partial P}{\partial y} \frac{dy}{dt}+\frac{\partial P}{\partial t}[/tex]
The Last piece is just a bit of notational detritus since [itex]P[/itex] is actually a function of [itex]x[/itex]
too you write the derivative on the left as partials
[tex]\frac{\partial }{\partial t} P(y(x,t), t) = \frac{\partial P}{\partial y} \frac{dy}{dt}+\frac{\partial P}{\partial t}[/tex]
but you have to remember that [itex]\frac{\partial }{\partial t}[/itex] has different meanings on each side
of the equation. on the left it is holding x constant while on the right it is holding y constant.
 
  • #3
That makes perfect sense now, thanks a lot!
 

1. What is a Fokker Planck solution biased random walk?

A Fokker Planck solution biased random walk is a mathematical model used to describe the behavior of a random walker in a biased environment. It takes into account both the random movements of the walker and any external forces or biases that may influence its path.

2. What is the Fokker Planck equation?

The Fokker Planck equation is a partial differential equation that describes the time evolution of a probability distribution for a random walker. It takes into account both the random diffusion of the walker and any drift or bias in its movement.

3. How is the Fokker Planck solution biased random walk used in scientific research?

The Fokker Planck solution biased random walk is used in various fields of science, including physics, chemistry, biology, and finance. It can be applied to understand the behavior of particles in a fluid, the movement of molecules in a cell, the spread of diseases, and the fluctuations in stock prices, among others.

4. What are some assumptions of the Fokker Planck solution biased random walk model?

Some common assumptions of the Fokker Planck solution biased random walk model include the absence of external forces, the independence of time and space scales, and the linearity of the drift and diffusion coefficients. These assumptions may not always hold true in real-world scenarios, but they allow for simpler mathematical calculations and analysis.

5. How does the Fokker Planck solution biased random walk differ from a regular random walk?

A regular random walk assumes that each step is equally likely in all directions, while a Fokker Planck solution biased random walk takes into account a bias or preference for certain directions. This bias can be caused by external forces, such as gravity or an electric field, or by internal factors, such as the previous movement of the walker. As a result, a biased random walk is more likely to move in a specific direction over time, while a regular random walk has no preferred direction.

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