Ej1 = 17
Ej2 = 22
Ec1 = 0.27
Ec2 = 0.27
g = 0.015 #/2pi
Q1 = Tunabletransmon(EC=Ec1, EJmax=Ej1)
Q2 = Tunabletransmon(EC=Ec2, EJmax=Ej2)
QQ = QQ(Q1, Q2, g)
#ini_state=iniState2Qsys(Q1.Nq,Q2.Nq,1,1)
Nq = 3
ini_coeff = [0, 1e-9, 0, 1e-9, 1, 0, 0, 0, 0] # 11
ini_state = ini_coeff[0]*qt.tensor(ket(Nq,0), ket(Nq,0)) \
+ ini_coeff[1]*qt.tensor(ket(Nq,0), ket(Nq,1)) \
+ ini_coeff[2]*qt.tensor(ket(Nq,0), ket(Nq,2)) \
+ ini_coeff[3]*qt.tensor(ket(Nq,1), ket(Nq,0)) \
+ ini_coeff[4]*qt.tensor(ket(Nq,1), ket(Nq,1)) \
+ ini_coeff[5]*qt.tensor(ket(Nq,1), ket(Nq,2)) \
+ ini_coeff[6]*qt.tensor(ket(Nq,2), ket(Nq,0)) \
+ ini_coeff[7]*qt.tensor(ket(Nq,2), ket(Nq,1)) \
+ ini_coeff[8]*qt.tensor(ket(Nq,2), ket(Nq,2))
Iq1 = qt.qeye(Nq)
Hq1_lab = QQ.Hq1 * (2 * pi)
rot2 = Hq(Q2.Nq, 0, abs(Q2.anh * (2 * pi)))
q2Freqs = qt.qdiags(np.arange(0, Q2.Nq, 1), 0)
Hq2_t_ind = qt.tensor(Iq1, rot2) #Hq2_rot(constant term)
Hq2_t_dep = qt.tensor(Iq1, q2Freqs) #Hq2_rot(modulation term)
def Hq(Nq, qFreq, qAnhar):
Hqs = 0
eigenFreq_list = [0, qFreq, 2 * qFreq - qAnhar]
for i in range(Nq):
Hqs = Hqs + eigenFreq_list[i] * (ket(Nq, i) * ket(Nq, i).dag())
return Hqs
Ej1 = 17
Ej2 = 22
Ec1 = 0.27
Ec2 = 0.27
g = 0.015 #/2pi
Q1 = Tunabletransmon(EC=Ec1, EJmax=Ej1, Nq=2)
Q2 = Tunabletransmon(EC=Ec2, EJmax=Ej2, Nq=2)
QQ = QQ(Q1, Q2, g)
#ini_state=iniState2Qsys(Q1.Nq,Q2.Nq,1,1)
Nq = 2
ini_coeff = [0, 1e-9, 1e-9, 1] # 11
ini_state = ini_coeff[0]*qt.tensor(ket(Nq,0), ket(Nq,0)) \
+ ini_coeff[1]*qt.tensor(ket(Nq,0), ket(Nq,1)) \
+ ini_coeff[2]*qt.tensor(ket(Nq,1), ket(Nq,0)) \
+ ini_coeff[3]*qt.tensor(ket(Nq,1), ket(Nq,1))
Iq1 = qt.qeye(Nq)
Hq1_lab = QQ.Hq1 * (2 * pi)
rot2 = Hq(Q2.Nq, 0, abs(Q2.anh * (2 * pi)))
q2Freqs = qt.qdiags(np.arange(0, Q2.Nq, 1), 0)
Hq2_t_ind = qt.tensor(Iq1, rot2) #Hq2_rot(constant term)
Hq2_t_dep = qt.tensor(Iq1, q2Freqs) #Hq2_rot(modulation term)
Hint = QQ.Hint12 * (2 * pi)
H_rot = [Hq1_lab + Hq2_t_ind + Hint, [Hq2_t_dep, MW_shaped]]
tgstart = 48
tgend = 48