Statistical weight for a degenerate system

In summary, we have proven that the expression for the statistical weight of a system of N particles with corresponding energy levels and degeneracy is W = N! / (No! N1! N2! ... Ni!).
  • #1
Andrew_
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Homework Statement



Find an expression of the statistical weight for a system of N particles of corresponding energy levels with 'gi' degeneracy.

Homework Equations



W = N! / No! N1!2! ...Ni!

The Attempt at a Solution



The expression is then :

W = N! goNo g1N1 g2N2 ... giNi / No! N1! N2! ...Ni!

However, I can't prove it. Can you help ?
 
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  • #2


I would like to offer some assistance in proving this expression for the statistical weight of a system of N particles with corresponding energy levels and degeneracy.

First, let's define some terms. The statistical weight, denoted by W, is a measure of the number of ways in which a given state can be realized in a system. In this case, we are considering a system of N particles with corresponding energy levels, each with a degeneracy of gi. This means that there are gi possible states for each energy level.

Next, let's consider the total number of particles, N, and the number of particles in each energy level, denoted by Ni. We can express the total number of particles as the sum of particles in each energy level, so N = N0 + N1 + N2 + ... + Ni.

Now, to prove the expression for the statistical weight, we can use the definition of permutation, which is the number of ways in which a set of objects can be arranged. In this case, the objects are the particles and the arrangements represent the different states of the system.

Using the definition of permutation, we can express the statistical weight as follows:

W = (N0 + N1 + N2 + ... + Ni)! / (N0! N1! N2! ... Ni!)

However, we can also express the total number of particles in terms of the degeneracy of each energy level, since N = goNo + g1N1 + g2N2 + ... + giNi.

Substituting this into the expression for W, we get:

W = (goNo + g1N1 + g2N2 + ... + giNi)! / (N0! N1! N2! ... Ni!)

Using the property of factorial, which states that (a + b)! = a! b!, we can simplify this expression to:

W = (N!) / (N0! N1! N2! ... Ni!)

And finally, using the definition of factorial, we can rewrite this expression as:

W = N! / (No! N1! N2! ... Ni!)

This proves the expression for the statistical weight of a system of N particles with corresponding energy levels and degeneracy. I hope this helps!
 

1. What is statistical weight for a degenerate system?

Statistical weight for a degenerate system is the measure of the number of ways a system can be arranged or occupied, taking into account the degeneracy of the energy levels. It is used in statistical mechanics to calculate the probability of a system being in a certain energy state.

2. How is statistical weight related to entropy?

Statistical weight is directly related to entropy, as it is used to calculate the entropy of a system. The higher the statistical weight, the higher the entropy, and vice versa. This is because a higher statistical weight indicates a higher number of possible microstates, leading to a higher degree of disorder or randomness in the system.

3. Can statistical weight be negative?

No, statistical weight cannot be negative. It is a positive quantity that represents the number of possible arrangements or occupations of a system. Negative statistical weight would not make physical sense and would violate the laws of thermodynamics.

4. How is statistical weight calculated?

Statistical weight is calculated by taking the product of the degeneracy of each energy level in the system. For example, if a system has two energy levels with degeneracies of 3 and 2, the statistical weight would be 3 x 2 = 6. This reflects the fact that there are 6 possible ways for the system to be arranged or occupied.

5. Why is statistical weight important in statistical mechanics?

Statistical weight is important in statistical mechanics because it allows us to calculate the probability of a system being in a certain energy state. This is crucial in understanding the behavior of systems at the microscopic level, and how they transition between different energy states. It also helps us calculate important thermodynamic quantities such as entropy, free energy, and heat capacity.

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