Stat mech and binomial distribution

In summary, the conversation discusses the probability of choosing particles of two different species, A and B, with probabilities p_A and p_B respectively, and the probability of N_A out of N particles being of type A. The solution involves using the binomial distribution, the Stirling approximation, and the central limit theorem for large N. The CLT can be applied directly by using the Linderberg version, but a simpler formulation may be needed since it is not stated formally in the book.
  • #1
erogard
62
0

Homework Statement



Suppose that particles of two different species, A and B, can be chosen with
probability p_A and p_B, respectively.

What would be the probability p(N_A;N) that N_A out of N particles are of type A?

The Attempt at a Solution



I figured this would correspond to a binomial distrib:

[tex]p_N(N_A) = \frac{N!}{N_A ! (N-N_A)!} p_A^{N_A} p_B^{N-N_A}[/tex]

Now I'm asked to consider the case where N gets large. Then I need to find [tex]p(N_A;N)[/tex] using 1) Stirling appox. and 2) the central limit theorem.

Not sure how to approach 1) since there are no log in my expression. Actually I don't quite get how to do 2) either. Any help would be much appreciated.
 
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  • #2
1) You can introduce the logs! And then remove the logs by exponentiation after you've made the approximation.

2) You should just apply the central limit theorem directly. Do you recall what the CLT says exactly?
 
  • #3
Matterwave said:
1) You can introduce the logs! And then remove the logs by exponentiation after you've made the approximation.

2) You should just apply the central limit theorem directly. Do you recall what the CLT says exactly?

So I did 1) by taking the log and exponentiating to simplify.

Regarding 2), I'm looking at http://en.wikipedia.org/wiki/Central_limit_theorem and I'm assuming the Linderberg version is the relevant one here. Not too sure how to apply it, however. Do you know of any simpler formulation of the theorem that would apply to my case? My book does not state it formally. Thanks!
 

Related to Stat mech and binomial distribution

1. What is statistical mechanics?

Statistical mechanics is a branch of physics that uses statistical methods to explain the behavior of a large number of particles in a system. It provides a bridge between the microscopic laws of physics and the macroscopic behavior of a system.

2. How is statistical mechanics related to thermodynamics?

Statistical mechanics is the microscopic foundation of thermodynamics. It explains how the macroscopic quantities of a thermodynamic system, such as temperature, pressure, and energy, arise from the behavior of individual particles at the microscopic level.

3. What is the binomial distribution?

The binomial distribution is a probability distribution that describes the number of successes in a fixed number of independent trials with a binary outcome (e.g. success or failure). It is often used to model real-world situations such as coin flips or medical trials.

4. How is the binomial distribution related to statistical mechanics?

In statistical mechanics, the binomial distribution arises as a result of the combinatorial nature of particles in a system. It is used to describe the distribution of particles in different energy states, which is essential for understanding the thermodynamic behavior of a system.

5. What are some applications of statistical mechanics and the binomial distribution?

Statistical mechanics and the binomial distribution have many applications in various fields, including physics, chemistry, biology, and engineering. They are used to study systems such as gases, liquids, and solids, as well as complex systems such as biological networks and financial markets.

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