Grand Canonical Partition Function for Simple System

The number of microstates is given by Pascal's triangle: \omega(n) = \binom{m}{n}. This means that you can write the grand canonical partition function as:\Xi = \sum_{n=0}^{m} \binom{m}{n} e^{-\beta(n \epsilon - \mu n)} where the first term in the exponent is the energy contribution and the second term is the contribution from the chemical potential. Simplifying this expression gives:\Xi = (1 + e^{-\beta(\epsilon - \mu)})^m In summary, to calculate the grand canonical partition function for a system with m lattice sites, you can use the general form \Xi = \sum_{
  • #1
PitchAintOne
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Homework Statement



I would like to calculate the grand canonical partition function (GCPF) for a system in which there are are [itex]m[/itex] lattice sites. A configuration may be specified by the numbers [itex](n_1, n_2, ... , n_m)[/itex], where [itex]n_k = 1[/itex] if a particle occupies site [itex]k[/itex] and [itex]n_k = 0[/itex] if no particle occupies site [itex]k[/itex]. Occupied sites have an associated energy [itex] \epsilon [/itex] (constant) and unoccupied sites have zero associated energy.

Homework Equations



The general form of the GCPF in my book (Chandler) is given like this:

[tex] \Xi = \sum_{\nu} e^{ -\beta E_{\nu} + \beta \mu N_{\nu} } [/tex]

where [itex]\nu[/itex] indicates a summation over all states. (I am confused as to what, exactly, is meant by a "state" in the context of this problem.)

The Attempt at a Solution



For a given state [itex]j[/itex] the number of particles is given by [itex] N_j = \sum_{j=1}^{m} n_i [/itex] (summing over all sites). For the same state [itex]j[/itex] the energy is given by [itex] E_j = \epsilon \sum_{i=1}^{m} n_i [/itex].

I'm unsure of the correct direction from here. Inserting the expressions for [itex] N_j [/itex] and [itex] E_j [/itex] into [itex] \Xi [/itex] creates a mess of summations. Is that the only way? Is it simplify-able?

I feel that I should be able to calculate the GCPF for just one site and then extend the result to [itex]m[/itex] sites since the sites are independent of one another. Is this possible? If so, how?

Thank you all.
 
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  • #2
A state is a set of occupation numbers (n_1,n_2,...,n_m) so when you sum over all possible states, you sum over configurations (0,0,...,0), (1,0,0,...,0), ... , (1,1,...,1). Luckily the system is quite symmetric, so you do not need to sum the states one by one. Instead, you can write the sum over the number of occupied sites like so:

[itex]\sum_{\nu} \rightarrow \sum_{n=0}^{m} \omega(n) [/itex]

where [itex]\omega(n) [/itex] is the density of states, ie. the number of microstates (n1,n2,...,nm) corresponding to the macrostate.
 

What is the Grand Canonical Partition Function for Simple System (GCPFSS)?

The Grand Canonical Partition Function for Simple System is a mathematical formula used in statistical mechanics to describe the thermodynamic properties of a system in thermal equilibrium with a reservoir. It takes into account the number of particles, the energy, and the volume of the system, as well as the chemical potential of the reservoir.

How is the GCPFSS calculated?

The GCPFSS is calculated by taking the sum over all possible states of the system, each weighted by a factor of e^(-β(E-μN)), where β is the inverse temperature, E is the energy, μ is the chemical potential, and N is the number of particles. This sum is then divided by the partition function Z, which is the sum over all possible states of the system without the weight factor.

What is the significance of the GCPFSS?

The GCPFSS allows us to calculate the thermodynamic properties of a system in equilibrium with a reservoir, such as the average number of particles, energy, and entropy. It also allows us to understand the behavior of a system at different temperatures and chemical potentials.

What are some applications of the GCPFSS?

The GCPFSS has many applications in physics and chemistry, such as in the study of gases, liquids, and solids. It is also used in the field of material science to understand the behavior of materials at different temperatures and pressures. In addition, it is an important tool in the study of phase transitions and critical phenomena.

Are there any limitations to the GCPFSS?

While the GCPFSS is a powerful tool for understanding the behavior of simple systems, it has some limitations. It assumes that the system is in thermal equilibrium with a reservoir and that the particles in the system do not interact with each other. Therefore, it may not accurately describe more complex systems or systems with strong interactions between particles.

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