Plots of Different Distribution Functions: Program 1

f(E, T) vs E for different T for FD

#f(E, T) vs E for different T for FD import numpy as np import matplotlib.pyplot as plt Ef, k = 0.2, 8.61e-5 Erange = np.linspace(0,2*Ef,1000) Trange = [1,50,200] def f(E, T): return 1.0 / (np.exp((E - Ef)/(k*T)) + 1.0 ) for T in Trange: plt.plot(Erange, f(Erange, T), label = 'T = '+str(T)) plt.legend() plt.title("F(E,T) vs E") plt.xlabel('$\epsilon$ in eV', fontsize = 16) plt.ylabel('$f(\epsilon)$', fontsize = 16) plt.savefig('plot.png') Run Code

Output 1

Plots of Different Distribution Functions: Program 2

f(E, T) vs E for different T for BE

#f(E, T) vs E for different T for BE import numpy as np import matplotlib.pyplot as plt Ef, k = 0.2, 8.61e-5 Erange = np.linspace(0,2*Ef,1000) Trange = [1,50,200] def f(E, T): return 1.0 / (np.exp((E - Ef)/(k*T)) - 1.0 ) for T in Trange: plt.plot(Erange, f(Erange, T), label = 'T = '+str(T)) plt.legend() plt.title("F(E,T) vs E") plt.xlabel('$\epsilon$ in eV', fontsize = 16) plt.ylabel('$f(\epsilon)$', fontsize = 16) plt.savefig('plot.png') Run Code

Output 2

Plots of Different Distribution Functions: Program 3

f(E) vs T for different E for FD

#f(E) vs T for different E for FD import numpy as np import matplotlib.pyplot as plt Erange = [0.29, 0.30, 0.31] Trange = np.linspace(10,200,1000) mu, k = 0.30, 8.61e-5 def f(E, T): return 1 / (np.exp((E - mu)/(k*T)) + 1 ) for E in Erange: plt.plot(Trange, f(E, Trange), label = 'E = '+str(E)) plt.legend() plt.title("F(E,T) vs T") plt.xlabel('Temp in K', fontsize = 16) plt.ylabel('$f(\epsilon)$', fontsize = 16) plt.savefig('plot.png') Run Code

Output 3