Partition function approximation

In summary: Another approach is to use mathematical tools such as Riemann sums and integrals to show that the density of states times dE approximates the discrete measure. Additionally, there are more detailed discussions of this topic in various textbooks and articles on statistical mechanics.
  • #1
homology
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So I've been wrestling with something I was reading in a stat mech text. It's the derivation of the partition function for an ideal gas but I imagine the technique is used again. The author starts with the partition function for a single particle but then approximates the sum as an integral.

I get the idea behind it, the particle is essentially a free particle in a big box and has nearly a continuum of states so the 'Boltzmann-like" function e^(-E/kt) is integrated against density of states.

But I've been trying to make it a bit more rigorous. One idea I wondered about was the use of a discrete measure and maybe showing that the density of states times dE (so D(E)dE) approximates the discrete measure that gives back the sum.

Or perhaps trying to set up some sort of less complicated limiting process where I can show the integral approximation breaks down.

Any ideas? Or, if you're familiar with a more detailed discussion of this feel free to recommend a text/article.

thanks in advance,

Kevin
 
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  • #2
One way to make the derivation more rigorous is to start from the Hamiltonian of the system, which describes the energy of the particles in the system. The partition function is then obtained by taking the trace of the exponential of the Hamiltonian and dividing it by the normalization constant. By expanding the exponential in a Taylor series and using the fact that terms with different energies are orthogonal one can show that the partition function is the sum of an integral and a series of delta-functions. This makes the approximation of the sum as an integral more precise.
 

Related to Partition function approximation

1. What is a partition function approximation?

A partition function approximation is a mathematical tool used in statistical mechanics to calculate the thermodynamic properties of a system. It is an approximation of the exact partition function, which is a sum of all possible states of a system at a given temperature, and is used to simplify calculations.

2. How is partition function approximation used in statistical mechanics?

In statistical mechanics, partition function approximation is used to calculate the average energy, heat capacity, and other thermodynamic properties of a system. It is also used to study phase transitions and other complex phenomena in physical systems.

3. What are the limitations of partition function approximation?

Partition function approximation is based on simplifying assumptions and may not accurately reflect the true behavior of a system. It is also limited to systems that can be described by a Boltzmann distribution and does not take into account quantum effects.

4. How is partition function approximation related to entropy?

The partition function is related to entropy through the Boltzmann equation, which states that the entropy of a system is proportional to the logarithm of the partition function. Partition function approximation is used to calculate the entropy of a system and therefore plays a crucial role in understanding the thermodynamics of a system.

5. Can partition function approximation be used for all types of systems?

No, partition function approximation is limited to systems that can be described by a Boltzmann distribution. It is not applicable to systems with strong correlations or quantum effects, and may not accurately describe systems with complex interactions or non-equilibrium processes.

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