Question about Quantum + Thermodynamic Perturbation theory

Click For Summary
SUMMARY

The discussion centers on the application of Quantum Perturbation Theory as outlined in Landau's Statistical Physics, specifically in chapter 32. The energy levels of a perturbed system are derived using the Hamiltonian \(\hat{H} = \hat{H}_0 + \hat{V}\), leading to an expression for free energy that incorporates perturbations. A key point of confusion arises regarding the manipulation of double sums in the free energy equation, particularly the transition from \(\sum_n \sideset{}{'}{\sum}_m \frac{\lvert V_{nm}\rvert^2 w_n}{E_n^{(0)} - E_m^{(0)}}\) to \(-\frac{1}{2} \sum_n \sideset{}{'}{\sum}_m \frac{\lvert V_{nm}\rvert^2 (w_m - w_n)}{E_n^{(0)} - E_m^{(0)}}\). The resolution involves recognizing a simple index renaming trick.

PREREQUISITES
  • Understanding of Hamiltonians in quantum mechanics
  • Familiarity with Gibbs canonical distribution
  • Knowledge of perturbation theory in quantum physics
  • Ability to manipulate summations and series in mathematical physics
NEXT STEPS
  • Study the derivation of Quantum Perturbation Theory in detail
  • Explore the implications of the Gibbs distribution in statistical mechanics
  • Learn about the normalization of the Gibbs canonical distribution
  • Investigate advanced techniques in manipulating double sums in quantum mechanics
USEFUL FOR

Physicists, graduate students in quantum mechanics, and researchers focusing on statistical physics and perturbation theory.

mSSM
Messages
31
Reaction score
1
The following comes from Landau's Statistical Physics, chapter 32.

Using a Hamiltonian
\hat{H} = \hat{H}_0 + \hat{V}
we get the following expression for the energy levels of a perturbed system, up to second order:
E_n = E_0^{(0)} + V_{nn} + \sideset{}{'}{\sum}_m \frac{\lvert V_{nm}\rvert^2}{E_n^{(0)} - E_m^{(0)}}.
The prime signifies that the sum is done over all m\neq n.

Substituting this into the equation (from the normalisation of the Gibbs canonical distribution):
e^{-F/T} = \sum_0 e^{-E_n/T}.

This expression is then logarithmized and expanded in powers of V/T, so that we get:
F = F_0 + \sum_n V_{nn} w_n + \sum_n \sideset{}{'}{\sum}_m \frac{\lvert V_{nm}\rvert^2 w_n}{E_n^{(0)} - E_m^{(0)}} - \frac{1}{2T} \sum_n V^2_{nn} w_n + \frac{1}{2T} \left( \sum_n V_{nn} w_n \right)^2,
where w_n = \exp\left\{(F_0 - E_n^{(0)}/T\right\} is the unperturbed Gibbs distribution.

We can now notice that
\sum_n V_{nn} w_n \equiv \overline{V}_{nn},
i.e., the sum is the mean of V avaraged over the quantum state and the statistical distribution.

And now this is where it gets interesting, and where I fail to see something. Landau writes, that you can rewrite the equation for the free energy above in the following way:
F = F_0 + \overline{V}_{nn} - \frac{1}{2} \sum_n \sideset{}{'}{\sum}_m \frac{\lvert V_{nm}\rvert^2 (w_m - w_n)}{E_n^{(0)} - E_m^{(0)}} - \frac{1}{2T} \left\langle (V_{nn} - \overline{V}_{nn})^2 \right\rangle

That makes perfect sense except for the part with the double-sum, where I don't understand how he obtains it:
\sum_n \sideset{}{'}{\sum}_m \frac{\lvert V_{nm}\rvert^2 w_n}{E_n^{(0)} - E_m^{(0)}}= -\frac{1}{2} \sum_n \sideset{}{'}{\sum}_m \frac{\lvert V_{nm}\rvert^2 (w_m - w_n)}{E_n^{(0)} - E_m^{(0)}}

Is that even correct, or did I miss something? Can you tell me how he gets there? I have also looked up his derivation of the Quantum Perturbation theory, but it does not help me with this particular problem, unfortunately.
 
Physics news on Phys.org
Split up the original double sum containing only w_n into two and rename the summation indices n<->m in the second one.
 
Oh dear, thank you so much! I was going crazy over this... :D This is such a silly trick.
 

Similar threads

  • · Replies 2 ·
Replies
2
Views
2K
  • · Replies 3 ·
Replies
3
Views
2K
  • · Replies 2 ·
Replies
2
Views
2K
  • · Replies 11 ·
Replies
11
Views
2K
  • · Replies 2 ·
Replies
2
Views
1K
  • · Replies 2 ·
Replies
2
Views
2K
  • · Replies 2 ·
Replies
2
Views
4K
  • · Replies 3 ·
Replies
3
Views
4K
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 1 ·
Replies
1
Views
2K