StatMech: Binomial approximation

In summary, the conversation discusses approximating the binomial distribution to get the Poisson distribution and deriving the formula N!/(N-n)!=N^n. The Stirling formula is mentioned as a potential method for finding the approximation, but the conversation ultimately leads to using a different approach by selectively using the approximation and discussing the role of exponential(-n) in the final answer.
  • #1
rsaad
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Homework Statement



The question requires me to approximate binomial distribution to get poisson distribution.
Show that N!/(N-n)!=N^n.

Homework Equations



N!/n!(N-n)! p^n q^(N-n)=Binomial distribution



The Attempt at a Solution



I expanded N!/(N-n)! and got: (N-1)(N-2)(N-3)...(N-n+2)(N-n+1). This didn't help me in getting the required approximation. So, then I wrote it as follows:( N-(n-(n-1)) ) ( N-( n- (n-2) ) )...( N-(n-2) ) ( N-(n-1) ).
It seem to have further complicated the question.
A little help please.:redface:
Thank you.
 
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  • #2
Look at how the Stirling formula is derived ... it should be quite helpful.
 
  • #3
I looked at the stirling formula derivation but I don't know how it is helpful here.
So I have solved it the other way.
[N-(n-(n-0))] [N-(n-(n-1))] [N-(n-(n-2))] [N-(n-(n-3))]...[N-( n-(3) )][N-( n-(2) )][N-( n-(1) )]
For N>>n, using this approximation once, I get n terms:
[N-n] [N-n] [N-n] ... [N-n] [N-n] [N-n]
using the approximation again,
[N] [N] [N] ...[N] [N] [N] =N^n

My question is can I use this approximation selectively like I did in the above two steps.
Secondly, how was sterling formula derivation helpful? I used the x! formula and I get exponential(-n). Because n<<N, this term is big, making the entire answer zero.
 

1. What is the binomial approximation in statistical mechanics?

The binomial approximation is a mathematical technique used in statistical mechanics to approximate the behavior of a complex system by considering only the most important and dominant terms in a large series expansion. This approximation is often used to simplify calculations and make them more manageable.

2. How is the binomial approximation different from other approximations?

The binomial approximation differs from other approximations in statistical mechanics because it is based on the binomial theorem, which provides a closed-form expression for the expansion of a binomial expression. This makes it a powerful tool for simplifying calculations and obtaining accurate results.

3. When is the binomial approximation used in statistical mechanics?

The binomial approximation is commonly used in statistical mechanics when dealing with large systems that involve many particles, such as in the study of gases or liquids. It is also used when the system is in a state of equilibrium, where the energy levels are not changing significantly.

4. What are the limitations of the binomial approximation?

While the binomial approximation is a useful tool, it does have its limitations. It assumes that the number of particles in the system is large, and that the energy levels are not changing significantly. It also assumes that the particles are non-interacting, which may not always be the case in real systems.

5. How can the accuracy of the binomial approximation be improved?

The accuracy of the binomial approximation can be improved by considering higher-order terms in the series expansion, which may be necessary for systems with a large number of particles. Additionally, incorporating corrections for particle interactions and energy level changes can also improve the accuracy of the approximation.

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