Python Programs for Bose-Einstein Distribution and Planck Law of Radiation
Learn about the implementation of the Bose-Einstein distribution and Planck's law of radiation through Python programming. Explore how these physical concepts are visualized and analyzed using numpy and matplotlib libraries.
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Ismail Sk Assistant Professor Department of Physics Bajkul Milani Mahavidyala Python Program, 6th Sem Lecture 1: 2 hrs Program 1: Bose Einstein distribution import numpy as np import matplotlib.pyplot as plt e=1.6e-19 # electric charge k=1.38e-23#Boltzman const E=np.linspace(-1,1,1001)#energy range u=0# chemical potential def Fn(T,a): return 1/((np.exp(((E-u)*e)/(k*T)))+a) #plot results plt.plot(E,Fn(10,-1),label='T=10K') plt.plot(E,Fn(100,-1),label='T=100K') plt.plot(E,Fn(400,-1),label='T=400K') plt.xlabel('E(ev)') plt.ylabel('f(E)') plt.title("Bose Einstein distribution for u=0") plt.show()
Program 2: Planck law of Radiation import numpy as np import matplotlib.pyplot as plt k=1.38e-23 #boltzman constant h=6.626e-34 c=3e+8 pi=3.14 L0=np.arange(0.1,10,0.005) #wave length in micro m L=L0*1e-6 #wavelength in m def Fn(L,T): a=(8*pi*h*c)/L**5 b=(h*c)/(L*k*T) c1=np.exp(b)-1 d=a/c1 return d #plot results plt.plot(L, Fn(L,500),label='T=500K') plt.plot(L, Fn(L,600),label='T=600K') plt.plot(L, Fn(L,900),label='T=900K') plt.plot(L, Fn(L,1200),label='T=1200K') plt.legend(loc="best" , prop={'size':12}) plt.xlabel("$\lambda$ ") plt.ylabel("U($\lambda $,T )") plt.title("Planck law of Radiation") plt.show()
