Stirling Approximation for a thermodynamic system

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Homework Help Overview

The discussion revolves around the Stirling approximation in the context of thermodynamics, specifically analyzing the ratio of ways to distribute particles in a room under different conditions. The original poster presents a problem involving the approximation and seeks assistance in deriving a specific ratio related to particle distribution.

Discussion Character

  • Exploratory, Assumption checking, Mathematical reasoning

Approaches and Questions Raised

  • Participants discuss the application of the Stirling approximation and its implications for calculating probabilities of particle distributions. There are attempts to clarify the correct formulation of the approximation and the algebra involved in deriving the ratio.

Discussion Status

The conversation includes various attempts to apply the Stirling approximation correctly, with some participants pointing out potential errors in algebra and notation. There is an ongoing exploration of how to simplify the expressions and extract the desired form of the answer, with no explicit consensus reached on the final outcome.

Contextual Notes

Participants note the importance of maintaining proper notation and parentheses in calculations. There is also mention of the asymptotic nature of the result, indicating that constant factors may not be critical for large values of n.

Demroz
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Homework Statement


The stirling approximation, J! = √JJ+1/2e-J, is very handy when dealing with numbers larger than about 100. consider the following ratio: the number of ways N particles can be evenly divided between two halves of a room to the number of ways they can be divided with 60% on the right and 40% on the left.

a. Show using the stirling approximation that the ratio is approximately (0.40.40.60.6/5)n

Homework Equations



N!/NR!(N - NR)!

J! = √JJ+1/2e-J

The Attempt at a Solution



So i figured out the ratio to be
(0.5n)!(0.4n)!/(0.5n)!

Then by using the stirling approximation I get

0.6n0.6n+1/20.4n0.4n+1/2 / 0.25nn+1

all of my attempts so far have given me that answer which simplifies to 24/25. can you guys point me in the right direction/show me what I'm doing wrong?
 
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Demroz said:
J! = √JJ+1/2e-J
No, it's ##J^Je^{-J}\sqrt{2\pi J}##. For the present problem the ##2\pi## doesn't matter since it will cancel, but the square root you have at the front is definitely wrong.
Demroz said:
So i figured out the ratio to be
(0.5n)!(0.4n)!/(0.5n)!
A typo in there?
Demroz said:
0.6n0.6n+1/20.4n0.4n+1/2 / 0.25nn+1
Not exactly sure what you mean by that since you've left out all the parentheses, but the 0.25 looks wrong. Please post your working, including all necessary parentheses.
 
Sorry about that, I screwed up a lot of things in typing it out

JJ+0.5e-J√2pi

My work

probability for a 50/50 distribution is

(N!)/((0.5N)!(0.5N)!)

probability for a 40/60 distribution

(N!)/((0.4N)!(0.6N)!)

when you divide 50/50 over 40/60 you get

((0.4N)!(0.6N)!)/((0.5N)!)2

So when I plug into the stirling approximation (I reworked it from the previous attempt)

((0.4n0.4n)(0.6n0.6n))/((2-n-1)(nn+1))

Which I was able to simplify to:

(0.40.4n0.60.6n)(2n+1)(n-n)

I have no idea where to go from here
 
Demroz said:
((0.4N)!(0.6N)!)/((0.5N)!)2
Agreed.
So when I plug into the stirling approximation (I reworked it from the previous attempt)

((0.4n0.4n)(0.6n0.6n))/((2-n-1)(nn+1))
That's not what I get. Please post all your working.
Demroz said:
I have no idea where to go from here
You can see from the question what form is required. After correcting the algebra so far, can you find a way to extract the n exponent to be outside as in the desired answer:
(0.40.40.60.6/5)n
You will find there is a constant factor that the n exponent does not apply to, but for these sorts of questions you don't have to worry about that. It's the asymptotic form that matters. E.g. 0.1n may be considered an approximation to 1000*0.1n for large n.
But btw, that answer is incorrect. It should be (0.40.40.60.6/0.5)n
 
I found what I did wrong, thank you very much for the help. It was a simple algebra mistake when distributing exponents
 

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