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Solutions lecture 7

Merged Lars kleyn Winkel requested to merge solutions-lecture-7 into master
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@@ -69,7 +69,7 @@ pyplot.xlabel('$ka$'); pyplot.ylabel(r'$E-\epsilon$')
pyplot.xlim([-2*pi,2*pi])
pyplot.ylim([-2*(t1-t2),2*(t1-t2)])
pyplot.xticks([-2*pi, -pi, 0, pi,2*pi], [r'$-2\pi$',r'$-\pi$', 0, r'$\pi$',r'$2\pi$'])
pyplot.yticks([-t1-t2, -np.abs(t1-t2), 0, np.abs(t1-t2), t1+t2], [r'$-t_1-t_2$',r'$-|t_1-t_2|$', '0', r'$|t_1-t_2|$', r'$t_1+t_2$']);
pyplot.yticks([-t1-t2, -np.abs(t1-t2), 0, np.abs(t1-t2), t1+t2], [r'$-t_1-t_2$',r'$|t_1-t_2|$', '0', r'$-|t_1-t_2|$', r'$t_1+t_2$']);
pyplot.vlines([-pi, pi], -2*(t1-t2)*1.1,2*(t1-t2)*1.1, linestyles='dashed');
pyplot.hlines([-np.abs(t1-t2), np.abs(t1-t2)], -2*pi, 2*pi, linestyles='dashed');
pyplot.fill_between([-3*pi,3*pi], -np.abs(t1-t2), np.abs(t1-t2), color='red',alpha=0.2);
@@ -89,8 +89,7 @@ Both $v_g$ and $m_{eff}$ can be calculated using the respective formulae given i
We know $g(E) = \frac{dN}{dk} \frac{dk}{dE} = \frac{L}{2\pi} \frac{1}{v_g}$ with $v_g$ from the previous subquestion. Graphically the density of states looks accordingly:
```python
pyplot.subplot(1,2,1)
pyplot.subplot(1,2,1)
pyplot.subplot(1,3,1)
k = np.linspace(-2*pi, 2*pi, 400)
t1 = 1;
t2 = 1.5;
@@ -105,7 +104,7 @@ pyplot.xlim([-2*pi,2*pi])
pyplot.xticks([-2*pi, -pi, 0, pi,2*pi], [r'$-2\pi$',r'$-\pi$', 0, r'$\pi$',r'$2\pi$'])
pyplot.yticks([-t1-t2, -np.abs(t1-t2), 0, np.abs(t1-t2), t1+t2], [r'$-t_1-t_2$',r'$-|t_1-t_2|$', '0', r'$|t_1-t_2|$', r'$t_1+t_2$']);
pyplot.subplot(1,2,2)
pyplot.subplot(1,3,2)
w = np.sqrt(t1**2 + t2**2+2*t1*t2*np.cos(k))
pyplot.hist(w,30, orientation='horizontal',ec='black',color='b');
pyplot.hist(-w,30, orientation='horizontal',ec='black',color='b');
@@ -114,6 +113,15 @@ pyplot.ylabel(r'$E-\epsilon$')
pyplot.yticks([],[])
pyplot.xticks([],[])
pyplot.tight_layout();
pyplot.subplot(1,3,3)
w = -(t1+t2)*np.cos(k/2)
pyplot.hist(w,60, orientation='horizontal',ec='black',color='r');
pyplot.xlabel(r'$g(E)$')
pyplot.ylabel(r'$E-\epsilon$')
pyplot.yticks([],[])
pyplot.xticks([],[])
pyplot.tight_layout();
```
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