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

# # QuTiP example: Quantum Process Tomography

# 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 numpy as np


# In[3]:


from qutip import *


# In[4]:


"""
Plot the process tomography matrices for some 1, 2, and 3-qubit qubit gates.
"""
gates = [['C-NOT', cnot()],
         ['SWAP', swap()],
         ['$i$SWAP', iswap()],
         ['$\sqrt{i\mathrm{SWAP}}$', sqrtiswap()],
         ['S-NOT', snot()],
         ['$\pi/2$ phase gate', phasegate(np.pi/2)],
         ['Toffoli', toffoli()],
         ['Fredkin', fredkin()]]


# In[5]:


def plt_qpt_gate(gate, figsize=(8,6)):

    name  = gate[0]
    U_psi = gate[1]
    
    N = len(U_psi.dims[0]) # number of qubits

    # create a superoperator for the density matrix
    # transformation rho = U_psi * rho_0 * U_psi.dag()
    U_rho = spre(U_psi) * spost(U_psi.dag())

    # operator basis for the process tomography
    op_basis = [[qeye(2), sigmax(), sigmay(), sigmaz()] for i in range(N)]

    # labels for operator basis
    op_label = [["$i$", "$x$", "$y$", "$z$"] for i in range(N)]

    # calculate the chi matrix
    chi = qpt(U_rho, op_basis)

    # visualize the chi matrix
    fig, ax = qpt_plot_combined(chi, op_label, name, figsize=figsize)
    
    ax.set_title(name)
    
    return fig, ax


# In[6]:


plt_qpt_gate(gates[0]);


# In[7]:


plt_qpt_gate(gates[1]);


# In[8]:


plt_qpt_gate(gates[2]);


# In[9]:


plt_qpt_gate(gates[3]);


# In[10]:


plt_qpt_gate(gates[4]);


# In[11]:


plt_qpt_gate(gates[5]);


# In[12]:


fig, ax = plt_qpt_gate(gates[6], figsize=(16,12))
ax.axis('tight');


# In[13]:


fig, ax = plt_qpt_gate(gates[7], figsize=(16,12))
ax.axis('tight');


# ## Versions

# In[14]:


from qutip.ipynbtools import version_table

version_table()