Quantum harmonic oscillator: average number of energy levels

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Homework Help Overview

The discussion revolves around calculating the average number of energy levels for a quantum harmonic oscillator at a given temperature T, utilizing the Boltzmann distribution and properties of geometric series. The original poster attempts to apply the trace of a density matrix in their calculations.

Discussion Character

  • Exploratory, Conceptual clarification, Mathematical reasoning

Approaches and Questions Raised

  • Participants discuss the normalization of probabilities and the calculation of the trace of a matrix. There are inquiries about expressing matrix elements in bra-ket notation and the implications of using the operator b+b in their calculations. Some participants also explore the effects of normalization factors on their results.

Discussion Status

The discussion is active, with participants providing guidance on normalization and the application of operators. There is an ongoing exploration of the mathematical expressions involved, with no explicit consensus reached on the final result yet.

Contextual Notes

Participants are navigating the complexities of quantum mechanics, particularly in the context of statistical mechanics and operator algebra. The need for normalization and the implications of the partition function are central to the discussion.

Earthland
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Homework Statement



I must find the average number of energy levels of quantum harmonic oscillator at temperature T, and the answer is given as

upload_2015-2-8_17-11-27.png


I must use Boltzmann distribution and the sum of geometric progression. For finding the average value I must use the equation

<F>=trace(F*rho)

Where rho is the density matrix, given as

upload_2015-2-8_17-15-39.png


Where p is the probability and n is the energy eigenstate of oscillator. For F I must use b+b

Homework Equations

The Attempt at a Solution


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upload_2015-2-8_17-30-31.png
 

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Your expression for p(n) needs to be normalized so that the sum of all probabilities equals 1.

If Amn are the matrix elements of a matrix A, how do you find the trace? If A is the matrix inside of your trace expression, can you find an explicit expression for Amn?
 
Last edited:
It would be sum ∑Amm over m
 
Earthland said:
It would be sum ∑Amm over m
Yes,

For an operator A, how would you express Amm in bra-ket notation?
 
That would be <m|A|m> . So applying that I think I would get

upload_2015-2-10_19-2-29.png


But still, how to apply b+b to that sum?
 
I got it wrong, <m|n>=kronecker's delta not unit matrix ... but that means I would lose the sum altogether!

EDIT:
Still wrong, the trace is also sum Σ<m|A|m> over m so in the end it should be the way I showed in the last post. But the question of b+b remains
 
Last edited:
You have neglected the effect of the operator ##b^{\dagger}b##. You can bring ##b^{\dagger}b## inside your sum over n and let it act on |n>.
 
That would bring n in front of |n> and I would get the sum:

upload_2015-2-10_19-28-32.png


But this is not geometric progression
 
Remember, you did not normalize your probabilities. So, your result so far is off by an overall normalization factor ##Z##. The first exponential in your result does not depend on the index n, so you can pull it out of the sum. You are left with$$\sum_{n=0}^{\infty} ne^{-n \beta \hbar \omega}$$ where ##\beta =1/ kT##.

The trick is to note that $$ne^{-n \beta \hbar \omega} = -\frac{1}{\hbar \omega} \frac{\partial }{\partial \beta}e^{-n \beta \hbar \omega}$$.
 
  • #10
Thank you. The sum of arithmetic-geometric series would yield the same result: http://en.wikipedia.org/wiki/Arithmetico-geometric_sequence#Sum_to_infinite_terms

I get

upload_2015-2-10_20-50-37.png


However, are you sure it is the right result? I can't see how it simplifies to
upload_2015-2-10_20-51-40.png
. Or do I just need some extra normalization?

Edit:

I think according to normalization I should just take

upload_2015-2-10_20-59-55.png


And I can see how it gives me the answer I require ;)
 
Last edited:
  • #11
Once you put in your normalization factor for the probabilities, you'll see that you'll get the desired result.
 
  • #12
  • #13
I need to divide the result with Z?
 
  • #14
Yes. It's important to understand that your original expressions for the p(n)'s needed to be divided by ##Z##.
 

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