#!/usr/bin/env python
# coding: utf-8

# # QuTiP example: Single-Qubit Dynamics

# J.R. Johansson and P.D. Nation
# 
# For more information about QuTiP see [http://qutip.org](http://qutip.org)

# In[1]:


get_ipython().run_line_magic('matplotlib', 'inline')


# In[2]:


import matplotlib.pyplot as plt


# In[3]:


import numpy as np


# In[4]:


from qutip import *


# In[5]:


def qubit_integrate(epsilon, delta, g1, g2, solver):

    H = epsilon / 2.0 * sigmaz() + delta / 2.0 * sigmax()
        
    # collapse operators
    c_ops = []

    if g1 > 0.0:
        c_ops.append(np.sqrt(g1) * sigmam())

    if g2 > 0.0:
        c_ops.append(np.sqrt(g2) * sigmaz())

    e_ops = [sigmax(), sigmay(), sigmaz()]
        
    if solver == "me":
        output = mesolve(H, psi0, tlist, c_ops, e_ops)  
    elif solver == "es":
        output = essolve(H, psi0, tlist, c_ops, e_ops)  
    elif solver == "mc":
        ntraj = 250
        output = mcsolve(H, psi0, tlist, ntraj, c_ops, [sigmax(), sigmay(), sigmaz()])  
    else:
        raise ValueError("unknown solver")
        
    return output.expect[0], output.expect[1], output.expect[2]


# In[6]:


epsilon = 0.0 * 2 * np.pi   # cavity frequency
delta   = 1.0 * 2 * np.pi   # atom frequency
g2 = 0.15
g1 = 0.0

# intial state
psi0 = basis(2,0)

tlist = np.linspace(0,5,200)

# analytics
sx_analytic = np.zeros(shape(tlist))
sy_analytic = -np.sin(2*np.pi*tlist) * np.exp(-tlist * g2)
sz_analytic = np.cos(2*np.pi*tlist) * np.exp(-tlist * g2)


# In[7]:


sx1, sy1, sz1 = qubit_integrate(epsilon, delta, g1, g2, "me")


# In[8]:


fig, ax = plt.subplots(figsize=(12,6))
ax.plot(tlist, np.real(sx1), 'r')
ax.plot(tlist, np.real(sy1), 'b')
ax.plot(tlist, np.real(sz1), 'g')
ax.plot(tlist, sx_analytic, 'r*')
ax.plot(tlist, sy_analytic, 'g*')
ax.plot(tlist, sz_analytic, 'g*')
ax.legend(("sx", "sy", "sz"))
ax.set_xlabel('Time')
ax.set_ylabel('expectation value');


# In[9]:


sx2, sy2, sz2 = qubit_integrate(epsilon, delta, 0, 0, "me")


# In[10]:


# analytics
sx_analytic = np.zeros(np.shape(tlist))
sy_analytic = -np.sin(2*np.pi*tlist)
sz_analytic = np.cos(2*np.pi*tlist)


# In[11]:


fig, ax = plt.subplots(figsize=(12,6))
ax.plot(tlist, np.real(sx2), 'r')
ax.plot(tlist, np.real(sy2), 'b')
ax.plot(tlist, np.real(sz2), 'g')
ax.plot(tlist, sx_analytic, 'r*')
ax.plot(tlist, sy_analytic, 'g*')
ax.plot(tlist, sz_analytic, 'g*')
ax.legend(("sx", "sy", "sz"))
ax.set_xlabel('Time')
ax.set_ylabel('expectation value');


# ## Bloch sphere

# In[12]:


w     = 1.0 * 2 * np.pi   # qubit angular frequency
theta = 0.2 * np.pi       # qubit angle from sigma_z axis (toward sigma_x axis)
gamma1 = 0.05      # qubit relaxation rate
gamma2 = 0.02      # qubit dephasing rate
# initial state
a = 1.0
psi0 = (a * basis(2,0) + (1-a)*basis(2,1))/(np.sqrt(a**2 + (1-a)**2))
tlist = np.linspace(0,15,1000)


# In[13]:


def qubit_integrate(w, theta, gamma1, gamma2, psi0, tlist):
    # Hamiltonian
    sx = sigmax()
    sy = sigmay()
    sz = sigmaz()
    sm = sigmam()
    H = w * (np.cos(theta) * sz + np.sin(theta) * sx)
    # collapse operators
    c_op_list = []
    n_th = 0.5 # zero temperature
    rate = gamma1 * (n_th + 1)
    if rate > 0.0:
        c_op_list.append(np.sqrt(rate) * sm)
    rate = gamma1 * n_th
    if rate > 0.0:
        c_op_list.append(np.sqrt(rate) * sm.dag())
    rate = gamma2
    if rate > 0.0:
        c_op_list.append(np.sqrt(rate) * sz)
    # evolve and calculate expectation values
    output = mesolve(H, psi0, tlist, c_op_list, [sx, sy, sz])  
    return output.expect[0], output.expect[1], output.expect[2]


# In[14]:


sx, sy, sz = qubit_integrate(w, theta, gamma1, gamma2, psi0, tlist)


# In[15]:


sphere=Bloch()
sphere.add_points([sx,sy,sz], meth='l')
sphere.vector_color = ['r']
sphere.add_vectors([np.sin(theta), 0, np.cos(theta)])
sphere.show()


# ## Versions

# In[16]:


from qutip.ipynbtools import version_table

version_table()