我一直在尝试使用 QuTiP 来求解量子力学矩阵微分方程(Lindblad 方程)。这是代码:
from qutip import *
from matplotlib import *
import numpy as np
hamiltonian = np.array([[215, -104.1, 5.1, -4.3 ,4.7,-15.1 ,-7.8 ],
[-104.1, 220.0, 32.6 ,7.1, 5.4, 8.3, 0.8],
[ 5.1, 32.6, 0.0, -46.8, 1.0 , -8.1, 5.1],
[-4.3, 7.1, -46.8, 125.0, -70.7, -14.7, -61.5],
[ 4.7, 5.4, 1.0, -70.7, 450.0, 89.7, -2.5],
[-15.1, 8.3, -8.1, -14.7, 89.7, 330.0, 32.7],
[-7.8, 0.8, 5.1, -61.5, -2.5, 32.7, 280.0]])
H=Qobj(hamiltonian)
ground=Qobj(np.array([[ 0.0863685 ],
[ 0.17141713],
[-0.91780802],
[-0.33999268],
[-0.04835763],
[-0.01859027],
[-0.05006013]]))
rho0 = ground*ground.dag()
from scipy.constants import *
ktuple=physical_constants['Boltzmann constant in eV/K']
k = ktuple[0]* 8065.6
htuple = physical_constants['Planck constant in eV s']
hbar = (htuple[0]* 8065.6)/(2*pi)
gamma=(2*pi)*((k*300)/hbar)*(35/(150*hbar))
L1 = Qobj(np.array([[1,0,0,0,0,0,0],[0,0,0,0,0,0,0],[0,0,0,0,0,0,0],[0,0,0,0,0,0,0],[0,0,0,0,0,0,0],[0,0,0,0,0,0,0],[0,0,0,0,0,0,0]]))
L2 = Qobj(np.array([[0,0,0,0,0,0,0],[0,1,0,0,0,0,0],[0,0,0,0,0,0,0],[0,0,0,0,0,0,0],[0,0,0,0,0,0,0],[0,0,0,0,0,0,0],[0,0,0,0,0,0,0]]))
L3 = Qobj(np.array([[0,0,0,0,0,0,0],[0,0,0,0,0,0,0],[0,0,1,0,0,0,0],[0,0,0,0,0,0,0],[0,0,0,0,0,0,0],[0,0,0,0,0,0,0],[0,0,0,0,0,0,0]]))
L4 = Qobj(np.array([[0,0,0,0,0,0,0],[0,0,0,0,0,0,0],[0,0,0,0,0,0,0],[0,0,0,1,0,0,0],[0,0,0,0,0,0,0],[0,0,0,0,0,0,0],[0,0,0,0,0,0,0]]))
L5 = Qobj(np.array([[0,0,0,0,0,0,0],[0,0,0,0,0,0,0],[0,0,0,0,0,0,0],[0,0,0,0,0,0,0],[0,0,0,0,1,0,0],[0,0,0,0,0,0,0],[0,0,0,0,0,0,0]]))
L6 = Qobj(np.array([[0,0,0,0,0,0,0],[0,0,0,0,0,0,0],[0,0,0,0,0,0,0],[0,0,0,0,0,0,0],[0,0,0,0,0,0,0],[0,0,0,0,0,1,0],[0,0,0,0,0,0,0]]))
L7 = Qobj(np.array([[0,0,0,0,0,0,0],[0,0,0,0,0,0,0],[0,0,0,0,0,0,0],[0,0,0,0,0,0,0],[0,0,0,0,0,0,0],[0,0,0,0,0,0,0],[0,0,0,0,0,0,1]]))
#Since our gamma variable cannot be directly applied onto the Lindblad operator, we must multiply it with the collapse operators:
L1=gamma*L1
L2=gamma*L2
L3=gamma*L3
L4=gamma*L4
L5=gamma*L5
L6=gamma*L6
L7=gamma*L7
options = Options(nsteps=100000)
results = mesolve(H, rho0, np.linspace(0.0, 1000, 20),[L1,L2,L3,L4,L5,L6,L7],[],options=options)
print results
此代码应该解决以下等式:
其中 L_i 是矩阵(在列表中:[L1,L2,L3,L4,L5,L6,L7]),H 是哈密顿矩阵,另一个矩阵是密度矩阵,并且是一个常数,其中 T 是温度, k 是玻尔兹曼常数, , 其中 h 是普朗克常数。
每次我运行代码时,都会出现以下错误:
ZVODE-- At T (=R1) and step size H (=R2), the
corrector convergence failed repeatedly
or with abs(H) = HMIN
In above, R1 = 0.0000000000000D+00 R2 = 0.1202322246215D-36
/usr/local/lib/python2.7/dist-packages/scipy/integrate/_ode.py:853: UserWarning: zvode: Repeated convergence failures. (Perhaps bad Jacobian supplied or wrong choice of MF o
r tolerances.)
'Unexpected istate=%s' % istate))
Traceback (most recent call last):
File "lindbladqutip.py", line 48, in <module>
results = mesolve(H, rho0, np.linspace(0.0, 1000, 20),[L1,L2,L3,L4,L5,L6,L7],[],options=options)
File "/projects/d6138712-e5f4-4d85-9d4d-77ce0a7b4a61/.local/lib/python2.7/site-packages/qutip/mesolve.py", line 264, in mesolve
progress_bar)
File "/projects/d6138712-e5f4-4d85-9d4d-77ce0a7b4a61/.local/lib/python2.7/site-packages/qutip/mesolve.py", line 692, in _mesolve_const
return _generic_ode_solve(r, rho0, tlist, e_ops, opt, progress_bar)
File "/projects/d6138712-e5f4-4d85-9d4d-77ce0a7b4a61/.local/lib/python2.7/site-packages/qutip/mesolve.py", line 866, in _generic_ode_solve
raise Exception("ODE integration error: Try to increase "
Exception: ODE integration error: Try to increase the allowed number of substeps by increasing the nsteps parameter in the Options class.
在做了一些调试分析之后,似乎第一次或第二次集成失败了。该错误告诉我增加我尝试过的 nsteps 参数。即使那样它也失败了。更改时间列表(np.linspace 函数生成时间列表)也没有效果。
我很想知道我能做些什么来解决这个错误。如果大家需要更多详细信息,请发表评论。
感谢你的帮助!