Variance in particle number

In summary, the equation states that the mean partice number in terms of the grandcanonical partition function is given by:\langle N \rangle = k_B T \frac{1}{Z} \frac{dZ}{d \mu}.
  • #1
cryptist
121
1
I saw an equation on wikipedia: (http://en.wikipedia.org/wiki/Fermi-Dirac_statistics)

b17305ed57f454a2e9b8a2ef47dd3f82.png


Does anybody know how this is derived?
 
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  • #2
Express the mean partice number in therms of the grandcanonical partition function.
 
  • #3
[itex]\langle N \rangle[/itex] is the Fermi-Dirac distribution, which is derived on that wikipedia page. So, you can perform the derivative yourself and verify the second equality.

The first equality can be derived as follows. First,

[itex]\displaystyle \langle ( \Delta N )^2 \rangle = \langle (N - \langle N \rangle )^2 \rangle = \langle N^2 - 2 \langle N \rangle N + \langle N \rangle^2 \rangle = \langle N^2 \rangle - \langle N \rangle^2[/itex].

Next, at constant volume and temperature, the grand-canonical partition function is given as the sum over all states, [itex]s[/itex] of the Gibbs factors, [itex]e^{- (e_s - \mu n_s ) / k_B T}[/itex] (check out the wikipedia page on partition function if this is unfamiliar):

[itex]\displaystyle Z = \sum_s e^{- (e_s - \mu n_s )/ k_B T}[/itex].

Here [itex]e_s[/itex] and [itex]n_s[/itex] are the state energy and occupation number. The Gibbs factor of a state measures the relative probability that that state is occupied. Hence, by definition,

[itex]\displaystyle \langle N \rangle = \frac{\sum_s n_s e^{-(e_s - \mu n_s)/k_B T}}{\sum_s e^{- (e_s - \mu n_s ) / k_B T}}[/itex].

Given these formulas for [itex]Z[/itex] and [itex]\langle N \rangle[/itex], you should be able to show that

[itex]\displaystyle \langle N \rangle = k_B T \frac{1}{Z} \frac{dZ}{d \mu}[/itex].

I've taken it for granted that the derivatives are taken at constant volume and temperature.

Analogously, show that

[itex] \displaystyle \langle N^2 \rangle = (k_B T)^2 \frac{1}{Z} \frac{d^2 Z}{d \mu^2} [/itex].

Okay. At this point, I think you have all of the formulas you need to derive the first equality that you quoted from wikipedia. Just a little bit of ingenuity left. Good luck.
 
  • #4
Thank you for the answer!
 

1. What is Variance in Particle Number?

Variance in particle number is a measure of the spread or variability in the number of particles present in a given sample or population. It is a statistical concept that quantifies the differences between individual values in a dataset, and the average or mean value.

2. Why is Variance in Particle Number important?

Variance in particle number is important because it provides valuable information about the distribution of particles in a sample. It can help scientists understand the level of heterogeneity in a population and make predictions about the behavior of the particles.

3. How is Variance in Particle Number calculated?

Variance in particle number is calculated by taking the sum of the squared differences between each data point and the mean, and then dividing by the total number of data points. This value is known as the variance and is typically represented by the symbol σ².

4. What factors can affect the Variance in Particle Number?

The Variance in particle number can be affected by a variety of factors such as the size and type of particles, the method of measurement, and the overall variability in the sample. Other factors such as experimental conditions and human error can also contribute to variability in particle number.

5. How can Variance in Particle Number be reduced?

To reduce the Variance in particle number, scientists can use techniques such as controlling experimental conditions, increasing the sample size, and using more precise measurement methods. It is also important to carefully select and prepare samples to minimize any sources of variability.

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