Average Energy for n-State Systems?

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SUMMARY

The discussion focuses on calculating the average energy ##\langle E \rangle## for an n-state system and a harmonic oscillator. For the n-state system, the average energy is derived from the weighted sum of probabilities using the Boltzmann distribution, resulting in the expression $$\langle E \rangle = \sum_{n=0}^n nε~e^{-nεβ}$$. The solution involves recognizing that the term can be evaluated using the derivative of the exponential function, leading to a geometric series for summation. This method is essential for both finite and infinite state systems.

PREREQUISITES
  • Understanding of Boltzmann distribution and its application in statistical mechanics.
  • Familiarity with the concept of average energy in thermodynamic systems.
  • Knowledge of geometric series and their properties.
  • Basic calculus, specifically differentiation and summation techniques.
NEXT STEPS
  • Study the derivation of the Boltzmann distribution in detail.
  • Learn about geometric series and their applications in statistical mechanics.
  • Explore advanced techniques for evaluating infinite series and sums.
  • Investigate the implications of temperature on energy distributions in physical systems.
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Students and professionals in physics, particularly those studying statistical mechanics, thermodynamics, and quantum mechanics, will benefit from this discussion.

danyull
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Homework Statement


Find the average energy ##\langle E \rangle## for
(a) an n-state system in which a given state can have energy 0, ε, 2ε, 3ε... nε.
(b) a harmonic oscillator, in which a state can have energy 0, ε, 2ε, 3ε... (i.e. with no upper limit).

Homework Equations


Definition of temperature: ##β = \frac 1 {K_BT} = \frac {d lnΩ(E)} {dE}##
Boltzmann distribution: ##P(ε) ∝ e^{-εβ}##

The Attempt at a Solution


Since the energy here takes on discrete values, the average is found by taking the weighted sum of the probabilities, $$\langle E \rangle = \sum_{n=0}^n nε~e^{-nεβ}$$
and in the case of part (b), the sum goes to infinity. My problem is I don't know how to evaluate these sums. Any help would be appreciated, thanks!
 
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One commonly used trick to evaluate such sums is the following observation that
<br /> n\varepsilon\,e^{-n\varepsilon \beta} = - \frac{\partial}{\partial \beta } (e^{-n\varepsilon \beta})<br />
and use the fact that the partial derivative commutes with the summation to get
<br /> \sum_{n=0}^{N} n\varepsilon\,e^{-n\varepsilon \beta} = - \frac{\partial}{\partial \beta } \sum_{n=0}^{N} e^{-n\varepsilon \beta}<br />
The summation is now simply just a geometric series.
(and don't forget to normalize your expectation value)
 
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