04.08.2013 Views

Statistical Mechanics - Physics at Oregon State University

Statistical Mechanics - Physics at Oregon State University

Statistical Mechanics - Physics at Oregon State University

SHOW MORE
SHOW LESS

You also want an ePaper? Increase the reach of your titles

YUMPU automatically turns print PDFs into web optimized ePapers that Google loves.

250 APPENDIX A. SOLUTIONS TO SELECTED PROBLEMS.<br />

<br />

<br />

1<br />

1 − k e B T (N∆−µ) + 1<br />

1<br />

e 1<br />

k B T ((N+1)∆−µ) + 1<br />

N<br />

i=1<br />

∞<br />

1 −<br />

e<br />

i=N+1<br />

k B T (N∆−µ) + 1<br />

1 − k e B T (i∆−µ) + 1<br />

<br />

e 1<br />

<br />

k B T ((N+1)∆−µ)<br />

e 1<br />

k B T (i∆−µ) + 1<br />

When the temper<strong>at</strong>ure is small, the sums go to one and we have:<br />

1<br />

1 − k e B T (N∆−µ) + 1 =<br />

1<br />

e 1<br />

k B T ((N+1)∆−µ) + 1<br />

1 − k e B T (N∆−µ) + 1 = e 1<br />

kB T ((N+1)∆−µ) + 1<br />

− 1<br />

1<br />

(N∆ − µ) = ((N + 1)∆ − µ)<br />

kBT kBT<br />

−(N∆ − µ) = ((N + 1)∆ − µ)<br />

which gives the desired result, since <strong>at</strong> T = 0 µ = ɛF . In words, for low temper<strong>at</strong>ure<br />

the amount on electrons leaving the st<strong>at</strong>e i = N is equal to the amount<br />

gained in i = N + 1, and fF D(µ + x; T, µ) + fF D(µ − x; T, µ) = 1<br />

Problem 7.<br />

The entropy for a system of independent Fermions is given by<br />

<br />

S = −kB (fF D log(fF D) + (1 − fF D) log(1 − fF D))<br />

o<br />

Calcul<strong>at</strong>e lim<br />

T →0 fF D(ɛ, T, µ) for ɛ < µ ,ɛ = µ , and ɛ > µ.<br />

fF D(ɛ, T, µ) =<br />

1<br />

e β(ɛ−µ) + 1<br />

fF D(µ, T, µ) = 1<br />

2<br />

Therefore, the limits are 1, 1<br />

2 , and 0, respectively.<br />

The number of orbitals with energy ɛo equal to the Fermi energy ɛF is M.<br />

Calcul<strong>at</strong>e the entropy <strong>at</strong> T = 0 in this case.<br />

<br />

1<br />

S = −kBM<br />

2 log(1<br />

1<br />

) +<br />

2 2 log(1<br />

2 )<br />

<br />

=<br />

<br />

= kB log(2 M )<br />

Explain your answer in terms of a multiplicity function. Pay close <strong>at</strong>tention to<br />

the issue of dependent and independent variables.

Hooray! Your file is uploaded and ready to be published.

Saved successfully!

Ooh no, something went wrong!