Boundary value problem- Random Walker

In summary: You solved this recurrence relation correctly in your original post; your error was to describe P_n as "probability of being at n" rather than "probabilty of reaching 0 given being at n".
  • #1
potatocake
6
1
Homework Statement
A walker performs a random walk on the grid points from 0 to N. Each time he tosses a fair coin, he moves one step forward if it is a head otherwise he moves one step backward. The random walk stops when the walker is at either 0 or N. What is the probability that the walker ends up at 0 given that he begins at i?
Relevant Equations
let the probability of the walker at i point to be P_i , P_0 = 1, P_N =0
I want to solve this using difference equation. So I set up the general equation to be
Pi = 0.5 Pi+1 + 0.5 i-1

I changed it to euler's form pi = z
0.5z2-z+0.5 = 0
z = 1
since z is a repeated real root
I set up general formula
Pn = A(1)n+B(1)n
then
P0 = A = 1
PN = A+BN = 0 -> A= -BN

This gives a general formula
Pn = 1- 1/N *n

However, I have no idea how I can show the probability that the walker ends up at 0 given that he begins at i. would it still be 1?
 
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  • #2
You've calculated [itex]P_n[/itex] as the probability that the walker reaches 0 given that he is at position [itex]n[/itex], even if you didn't acutally define it that way. So you're done.
 
  • #3
potatocake said:
let the probability of the walker at i point to be P_i , P_0 = 1, P_N =0
You can't define the probability of being at a particular point this way. There will be a probability of being at a particular point given having been at some other specified point some specified number of steps earlier.
Indeed, having set P0 to 1 the probability of being anywhere else must be zero.
Since the problem specifies starting at 1, you can define Pk(n) as the probability of being at n after k steps. Then P0(1)=1, etc.

But a more convenient approach is turn it around and let Pn be the probability of terminating at 0 given that we start at n. That avoids having to specify the number of steps. I think you'll find the algebra largely the same as you wrote.
potatocake said:
since z is a repeated real root
I set up general formula
Pn = A(1)n+B(1)n
I think you left out a factor n on one term.
potatocake said:
This gives a general formula
Pn = 1- 1/N *n
I assume you mean 1-n/N, but that does not give a probability distribution since it does not sum to 1.
 
  • #4
I assume you mean 1-n/N, but that does not give a probability distribution since it does not sum to 1.

Does that mean my general formula is wrong?

But a more convenient approach is turn it around and let Pn be the probability of terminating at 0 given that we start at n. That avoids having to specify the number of steps. I think you'll find the algebra largely the same as you wrote

Does that mean I have to get
Pn(0) ?
 
  • #5
potatocake said:
Does that mean my general formula is wrong?
The entire method is wrong, as I indicated:
haruspex said:
You can't define the probability of being at a particular point this way. There will be a probability of being at a particular point given having been at some other specified point some specified number of steps earlier.
That said, I suspect you landed on the right answer by sheer luck. This is why @pasmith thought you had got there.
potatocake said:
Does that mean I have to get
Pn(0) ?
No, I may have confused you by completely redefining P. To avoid confusion I'll reword it:
haruspex said:
a more convenient approach is to turn it around and let Qn be the probability of terminating at 0 given that we start at n.
With this definition, what is the relationship between Qn-1, Qn and Qn+1?
 
Last edited:
  • #6
haruspex said:
With this definition, what is the relationship between Qn-1, Qn and Qn+1?
I suppose it will form
Qn = 0.5Qn+1+0.5Qn-1 ...?

then will the probability of terminating at 0 given that we start from 0 is
Q0 = 1
and probability of terminating at 0 given that we start from N is
QN = 0.5QN+1 + 0.5QN-1??

Then how would I solve the differential equation? Through iterations? or using Euler's form?
If QN does not give me a constant value, I don't have boundary conditions.
 
  • #7
potatocake said:
I suppose it will form
Qn = 0.5Qn+1+0.5Qn-1 ...?

then will the probability of terminating at 0 given that we start from 0 is
Q0 = 1
and probability of terminating at 0 given that we start from N is
QN = 0.5QN+1 + 0.5QN-1??

Then how would I solve the differential equation? Through iterations? or using Euler's form?
If QN does not give me a constant value, I don't have boundary conditions.

[itex]Q_N[/itex] is constant: it's zero. That's one of your boundary conditions, the other being [itex]Q_0 = 1[/itex]. You solved this recurrence relation correctly in your original post; your error was to describe [itex]P_n[/itex] as "probability of being at [itex]n[/itex]" rather than "probabilty of reaching 0 given being at [itex]n[/itex]".
 
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1. What is a boundary value problem in the context of a random walker?

A boundary value problem in the context of a random walker is a mathematical model that describes the behavior of a random walker as it moves within a defined boundary. The boundary can be physical, such as a wall or barrier, or abstract, such as a set of conditions or constraints.

2. How is a random walker's behavior affected by boundary conditions?

A random walker's behavior is affected by boundary conditions in that it must follow certain rules or constraints as it moves within the boundary. For example, if the boundary is a physical wall, the walker cannot pass through it. If the boundary is a set of conditions, the walker must follow those conditions as it moves.

3. What are some common applications of boundary value problems in random walker models?

Boundary value problems in random walker models have many applications, including studying diffusion processes, modeling animal movement patterns, and understanding the dynamics of financial markets. They can also be used in computer simulations to model complex systems.

4. How are boundary value problems solved in the context of random walkers?

Boundary value problems in the context of random walkers can be solved using various mathematical techniques, such as Monte Carlo simulations, random walk algorithms, and stochastic differential equations. These methods allow for the prediction of the walker's behavior and the analysis of its movement patterns.

5. What are some limitations of using boundary value problems in random walker models?

Some limitations of using boundary value problems in random walker models include the assumption of a well-defined boundary, which may not accurately reflect real-world scenarios. Additionally, the complexity of the boundary conditions and the randomness of the walker's movements can make it difficult to accurately predict behavior and outcomes.

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