我正在尝试在 qutip 中运行此代码。但它没有显示任何结果。但是没有显示任何错误。所有代码都是正确的，没有显示任何错误。但不知道为什么程序没有执行。如果有人能解决这个问题，非常欢迎。
from __future__ import division
from qutip import *
import pylab
import math
import matplotlib.pyplot as plt
import numpy as np
import csv
#import plotly.plotly as py
#from plotly.graph_objs import *
#py.sign_in("cayayald", "zlae2s4d1i")
#linewidth
#gamma = 1 => fully independent
#G = 1 => fully collective
gamma = .25
G = 1.0 - gamma
#delta is detuning
delta = -1
deltastep = 0.1
dlist = []
#n is number of atoms
n = 16
#V is energy shiftdue to dipole-dipole
V = 10
#omega is rabi freq
omega = 1.5
omegastep = 0
#lowering, raising, and state collapsing operators
sigmamlist = []
sigmaplist = []
c_op_list = []
for j in range (n):
if j==0:
sigmajm=sigmam()
else:
sigmajm=qeye(2)
for i in range (1,n):
if j == i:
sigmaj1= tensor(sigmam(),sigmajm)
else:
sigmajm = tensor(qeye(2),sigmajm)
sigmamlist.append(sigmajm)
coplist.append(math.sqrt(gamma)*sigmajm) #n-many indep collapse ops
sigmajp = sigmajm.dag()
sigmaplist.append(sigmajp)
coplist.append(math.sqrt(G)*sum(sigmamlist)) #one collective collapse op
#we want expectation values of operators in exoplist
exoplist = []
#numerator of cross correlation
exoplist.append(sigmaplist[0]*sigmamlist[0]*sigmaplist[1]*sigmamlist[1])
#denomenator of cross correlation
exoplist.append(sigmaplist[0]*sigmamlist[0])
exoplist.append(sigmaplist[1]*sigmamlist[1])
在此之后，下面的这些代码没有运行并且需要时间。不知道为什么？
#initial state vector
psi0 = basis(2,0)
for i in range(1,n):
psi0 = tensor(psi0,basis(2,0))
#build Hamiltonian
g2 = []
list = np.linspace(0,200,2000)
ntraj = 1
while delta <= 7:
glist = []
hlist = []
vlist = []
for i in range(n):
hlist.append(-delta*(sigmaplist[i]*sigmamlist[i])+ (omega / 2)*(sigmaplist[i] +
sigmamlist[i]))
for i in range(n):
for j in range(i):
vlist.append((V / (n - 1))*((sigmaplist[j]*sigmamlist[j])
*(sigmaplist[i]*sigmamlist[i])))
H = sum(hlist) + sum(vlist)
#monte carlo trajectory
montecar = mcsolve(H, psi0, tlist, coplist, exoplist, ntraj)
for i in range(len(montecar.expect[0])):
numerator = montecar.expect[0][i]
denomenator = montecar.expect[1][i]
denom2 = montecar.expect[2][i]
glist.append(numerator/(denomenator*denom2))
g2.append(sum(glist)/len(glist))
dlist.append(delta)
delta = delta + deltastep
x = np.arange(10)
fig = plt.figure()
ax = plt.subplot(111)
ax.plot(dlist, g2)
# Shink current axis by 20%
box = ax.get_position()
ax.set_position([box.x0, box.y0, box.width * 0.8, box.height])
plt.grid(True)
plt.show()