import matplotlib.pyplot as plt
import numpy as np

N = 10000
D_values = [1.8 + np.random.uniform(- 0.5e-2, 0.5e-2) for _ in range(N)]
lambda_values = [650e-3 + np.random.uniform(-1e-3, 1e-3) for _ in range(N)]
L_values = [np.random.normal(2.92e-2, 0.132e-2) + np.random.uniform(-0.5e-3, 0.5e-3) for _ in range(N)]

a_values = [2*D*l/L for D, l, L in zip(D_values, lambda_values, L_values)]
plt.hist(a_values, bins=100,  density = True)
plt.show()