J.R. Johansson and P.D. Nation
For more information about QuTiP see http://qutip.org
import numpy as np
from qutip import (about, qeye, qpt, qpt_plot_combined, sigmax, sigmay, sigmaz,
spost, spre)
from qutip_qip.operations import (cnot, fredkin, iswap, phasegate, snot,
sqrtiswap, swap, toffoli)
%matplotlib inline
"""
Plot the process tomography matrices for some 1, 2, and 3-qubit qubit gates.
"""
gates = [
["C-NOT", cnot()],
["SWAP", swap()],
["$i$SWAP", iswap()],
[r"$\sqrt{i\mathrm{SWAP}}$", sqrtiswap()],
["S-NOT", snot()],
[r"$\pi/2$ phase gate", phasegate(np.pi / 2)],
["Toffoli", toffoli()],
["Fredkin", fredkin()],
]
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
plt_qpt_gate(gates[0]);
plt_qpt_gate(gates[1]);
plt_qpt_gate(gates[2]);