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我正在模拟一个简单的 lambda 型三级原子（EIT 敏感性）。当探测场耦合在 |1> 和 |3> 之间并且控制场耦合在 |2> 和 |3> 之间时，结果与预期结果一致。替换字段的选择（探针耦合|2>和|3>，控制耦合|1>和|3>）结果不同。lambda系统不是对称的吗？

from qutip import *
import math
import numpy as np
from math import pi
import matplotlib.pyplot as plt
import scipy as sp

#########################
gamma_p = 1 # decay rate on probe transition
gamma_c = 1 # decay rate on coupling transition
gamma = 0.05 # ground coherence decay
deltaC = 0 # coupling field detuning
omegaP = 0.01 # Rabi freq. for probe
omegaC = 1.0 # Rabi freq. for control

##########################
# Define the levels and atomic projection operators
one, two, three = three_level_basis()
sig_11 = one * one.dag()
sig_22 = two * two.dag()
sig_33 = three * three.dag()
sig_13 = one * three.dag()
sig_23 = two * three.dag()
sig_12 = one * two.dag()
#################
# Creating collapse operators
c1 = np.sqrt(gamma_p)*sig_13 # 1-3 coherence decay
c2 = np.sqrt(gamma_c)*sig_23 # 2-3 coherence decay
c3 = np.sqrt(gamma)*sig_12 # 1-2 coherence decay
collapse = [c1,c2,c3]
#########################
# create list of delta_p values
deltalist = np.linspace(-3,3,200)
# empty list to save results
chi = [] # susceptibility
#####################
#Calculation loop
for deltaP in deltalist:
    H = -1/2*Qobj([[0,0,omegaP],[0,2*(deltaP -deltaC),omegaC],[omegaP, omegaC, 2*deltaP]])
    rho_ss = steadystate(H,collapse)
    chi.append(expect(sig_13,rho_ss))
##################
#Graphing Eit Results
plt.plot(deltalist,np.real(chi),label="Index n")
plt.plot(deltalist,np.imag(chi),label="Absorption")
plt.legend()
plt.xlabel("$\Delta_p$")
#plt.yticks([])
plt.show()

##############

#Now Replacing the Probe and Control Field Rabi frequency

#######
chi=[]
#Calculation loop
for deltaP in deltalist:
    H = -1/2*Qobj([[0,0,omegaC],[0,2*(deltaP -deltaC),omegaP],[omegaC, omegaP, 2*deltaP]])
    rho_ss = steadystate(H,collapse)
    chi.append(expect(sig_13,rho_ss))

###########
#Graphing Eit Results
plt.plot(deltalist,np.real(chi),label="Index n")
plt.plot(deltalist,np.imag(chi),label="Absorption")
plt.legend()
plt.xlabel("$\Delta_p$")
#plt.yticks([])
plt.show()
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