Statistical physics reflection principle

In summary, the conversation discusses the problem of a random walker in one dimension with an absorbing wall at a specific point. The goal is to calculate the probability of reaching a certain point in a given number of steps and to find the solution for diffusion with an absorbing wall at the origin. The discussion touches on the reflection principle and the use of Gaussian solutions with proper boundary conditions.
  • #1
Dr.Lecter
1
0

Homework Statement



Consider a random walker in one dimension, which can take right or left steps with equal probability. Assume that the walker starts at the location k>0 and there is an absorbing wall at point labelled as 0, that means if the walker reaches 0 the process stops and he stays there. Calculate the probability of reaching point m>0 in N steps. By taking continuum limit, find the solution to the diffusion in the presence of an absorbing wall at the origin.

The Attempt at a Solution



Actually this is an example of reflection principle (method of imagines boundary value problems.) However I couldn't figure out how its related. So if you give me hint to where should I start I'll be appreciated.
 
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  • #2
I'm assuming you know what to do without the absorbing wall (i.e. how to derive the appropriate diffusion equation and show that the solution is Gaussian of some particular width in the continuum limit etc. etc. etc.) The diffusion equation is linear and has a unique solution given complete and consistent boundary conditions. So, given some set of boundary conditions, the solution will always be some linear combination of same-width Gaussians. For an absorbing wall at 0, the boundary condition is that the probably of reaching 0 in 0 steps is 0. Up to a sign (and only one sign will make sense here) there is one unique linear combination of same-width Gaussians that gives the value 0 at the point 0.
 

1. What is the reflection principle in statistical physics?

The reflection principle in statistical physics is a mathematical tool used to calculate the probability of a particle reaching a certain position in space based on its initial position and velocity. It assumes that the particle's trajectory is reversible, meaning that it can move both forward and backward in time.

2. How is the reflection principle applied in statistical physics?

The reflection principle is applied in statistical physics by considering the probability of a particle reaching a certain position in space as the sum of the probabilities of all possible paths that could lead to that position. This includes both direct and mirror-reflected paths.

3. What are the assumptions underlying the reflection principle in statistical physics?

The reflection principle in statistical physics is based on the assumption that the particle's motion follows the laws of classical mechanics, that the particle's trajectory is reversible, and that the particle's initial position and velocity are known with certainty.

4. What are the limitations of the reflection principle in statistical physics?

The reflection principle in statistical physics is limited by the assumption that the particle's motion follows classical mechanics. In reality, particles at the microscopic level may exhibit quantum behavior, which cannot be accurately described by the reflection principle. Additionally, the reflection principle does not take into account the effects of external forces on the particle's trajectory.

5. In what other fields is the reflection principle used?

The reflection principle is not only used in statistical physics, but also in other fields such as quantum mechanics, optics, and probability theory. In quantum mechanics, it is used to calculate the probability of a particle tunneling through a barrier. In optics, it is used to calculate the intensity of light reflected off a surface. In probability theory, it is used to calculate the probability of a random walk returning to its starting point.

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