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import numpy as np
import matplotlib.pyplot as plt
import qutip
N = 15
taus = np.linspace(0,10.0,200)
a = qutip.destroy(N)
H = 2 * np.pi * a.dag() * a
# collapse operator
G1 = 0.75
n_th = 2.00 # bath temperature in terms of excitation number
c_ops = [np.sqrt(G1 * (1 + n_th)) * a, np.sqrt(G1 * n_th) * a.dag()]
# start with a coherent state
rho0 = qutip.coherent_dm(N, 2.0)
# first calculate the occupation number as a function of time
n = qutip.mesolve(H, rho0, taus, c_ops, e_ops=[a.dag() * a]).expect[0]
# calculate the correlation function G1 and normalize with n to obtain g1
G1 = qutip.correlation_2op_1t(H, rho0, taus, c_ops, a.dag(), a)
g1 = np.array(G1) / np.sqrt(n[0] * np.array(n))
plt.plot(taus, np.real(g1), 'b', lw=2)
plt.plot(taus, n, 'r', lw=2)
plt.title('Decay of a coherent state to an incoherent (thermal) state')
plt.xlabel(r'$\tau$')
plt.legend([
r'First-order coherence function $g^{(1)}(\tau)$',
r'Occupation number $n(\tau)$',
])
plt.show()
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