class BlochPlot():
'''
Dynamic plot context, intended for displaying geometries.
like removing axes, equal axis, dynamically tune your figure and save it.
Args:
figsize (tuple, default=(6,4)): figure size.
filename (filename, str): filename to store generated figure, if None, it will not save a figure.
Attributes:
figsize (tuple, default=(6,4)): figure size.
filename (filename, str): filename to store generated figure, if None, it will not save a figure.
ax (Axes): matplotlib Axes instance.
Examples:
with BlochPlot() as bp:
bp.ball.add_vectors([0.4, 0.6, 0.8])
'''
def __init__(self, figsize=(6, 4), filename=None, dpi=300):
self.figsize = figsize
self.filename = filename
self.ax = None
def __enter__(self):
from qutip import Bloch3d, Bloch
plt.ion()
self.fig = plt.figure(figsize=self.figsize)
self.ax = Axes3D(self.fig, azim=-30, elev=15)
self.ball = Bloch(axes=self.ax)
self.ball.zlabel = [r'$|N\rangle$', r'$|S\rangle$']
return self
def __exit__(self, *args):
self.ax.axis('off')
self.ax.set_aspect("equal")
#self.ball.make_sphere()
self.ball.make_sphere()
plt.close()
if self.filename is not None:
print('Press `c` to save figure to "%s", `Ctrl+d` to break >>' %
self.filename)
pdb.set_trace()
plt.savefig(self.filename, dpi=300)
else:
pdb.set_trace()
def add_polar(self, theta, phi, color=None):
self.ball.add_vectors(polar2vec([1, theta, phi]))
self.ball.vector_color.append(color)
def text(self, vec, txt, fontsize=14):
if len(vec) == 2:
vec = polar2vec(*vec)
self.ax.text(vec[0],
vec[1],
vec[2],
txt,
fontsize=fontsize,
va='center',
ha='center')
def func(f1, b, set):
"""
This function Perform the gate application on the initial state of qubit and then the state tomography,
at the same time compute the analytical bloch state.
INCOME:
f1="string", b="string"
fig_data="svg",fig_data2="svg"
"""
#### Create the bloch-sphere on qutip
b1 = Bloch()
b2 = Bloch()
## create the analyical quantum state and perform tranformation
## Add states to the bloch sphere and plot it
b1.add_states(analytic(f1, b))
if not set:
states = qtomography(f1, b)
b2.add_vectors(states)
else:
### implements for
states = qtomography_s(f1, b)
for i in states:
b2.add_points(i)
b2.add_vectors(np.average(states, axis=0))
###
b2.render()
fig_data = print_figure(b2.fig, 'svg')
b1.render()
fig_data2 = print_figure(b1.fig, 'svg')
#b1.show()
#b2.show()
b1.clear()
b2.clear()
return fig_data, fig_data2
def plot_quantum_state(amplitudes):
"""
Thin function to abstract the plotting on the Bloch sphere.
"""
bloch_sphere = Bloch()
vec = get_vector(amplitudes[0], amplitudes[1])
bloch_sphere.add_vectors(vec)
bloch_sphere.show()
bloch_sphere.clear()
def bloch_plot(self, points=None, F=None):
"""
Plot the current state on the Bloch sphere using
qutip.
"""
# create instance of 3d plot
bloch = Bloch(figsize=[9, 9])
bloch.add_vectors([0, 0, 1])
bloch.xlabel = ['$<F_x>$', '']
bloch.ylabel = ['$<F_y>$', '']
bloch.zlabel = ['$<F_z>$', '']
if self.spin == 'half':
if points is None:
# convert current state into density operator
rho = np.outer(self.state.H, self.state)
# get Bloch vector representation
points = self.get_bloch_vec(rho)
# Can only plot systems of dimension 2 at this time
assert len(
points
) == 3, "System dimension must be spin 1/2 for Bloch sphere plot"
# create instance of 3d plot
bloch = Bloch(figsize=[9, 9])
elif self.spin == 'one':
#points is list of items in format [[x1,x2],[y1,y2],[z1,z2]]
if points is None:
points = [getStars(self.state)]
bloch.point_color = ['g', 'r',
'b'] #ensures point and line are same colour
bloch.point_marker = ['o', 'd', 'o']
#bloch.point_color = ['g','r'] #ensures point and line are same colour
#bloch.point_marker = ['o','d']
for p in points:
bloch.add_points([p[0][0], p[1][0], p[2][0]])
bloch.add_points([p[0][1], p[1][1], p[2][1]])
bloch.add_points(p, meth='l')
'''
bloch.point_color = ['b','b'] #ensures point and line are same colour
bloch.point_marker = ['o','o']
for p in points:
bloch.add_points(p)
bloch.add_points(p, meth='l')
'''
# add state
#bloch.render(bloch.fig, bloch.axes)
#bloch.fig.savefig("bloch.png",dpi=600, transparent=True)
bloch.show()
def PlotStateQWP(InputState, qwpAngle):
OutputState = QWP(qwpAngle) @ InputState
pntsX = [
StateToBloch(QWP(th) @ InputState)[0] for th in arange(0, pi, pi / 64)
]
pntsY = [
StateToBloch(QWP(th) @ InputState)[1] for th in arange(0, pi, pi / 64)
]
pntsZ = [
StateToBloch(QWP(th) @ InputState)[2] for th in arange(0, pi, pi / 64)
]
pnts = [pntsX, pntsY, pntsZ]
bsph = Bloch()
bsph.add_points(pnts)
bsph.add_vectors(StateToBloch(OutputState))
bsph.add_vectors(StateToBloch(InputState))
return bsph.show()
def PlotStateAnalyzer(InputState, hwpAngle, qwpAngle):
QWPstate = QWP(qwpAngle) @ InputState
OutputState = HWP(hwpAngle) @ QWP(qwpAngle) @ InputState
pntsX = [
StateToBloch(QWP(th) @ InputState)[0] for th in arange(0, pi, pi / 64)
]
pntsY = [
StateToBloch(QWP(th) @ InputState)[1] for th in arange(0, pi, pi / 64)
]
pntsZ = [
StateToBloch(QWP(th) @ InputState)[2] for th in arange(0, pi, pi / 64)
]
pnts = [pntsX, pntsY, pntsZ]
pntsX2 = [
StateToBloch(HWP(th) @ QWP(qwpAngle) @ InputState)[0]
for th in arange(0, pi, pi / 64)
]
pntsY2 = [
StateToBloch(HWP(th) @ QWP(qwpAngle) @ InputState)[1]
for th in arange(0, pi, pi / 64)
]
pntsZ2 = [
StateToBloch(HWP(th) @ QWP(qwpAngle) @ InputState)[2]
for th in arange(0, pi, pi / 64)
]
pnts2 = [pntsX2, pntsY2, pntsZ2]
bsph = Bloch()
bsph.add_points(pnts)
bsph.add_points(pnts2)
bsph.add_vectors(StateToBloch(OutputState))
bsph.add_vectors(StateToBloch(InputState))
bsph.add_vectors(StateToBloch(QWPstate))
return bsph.show()
def bloch_plot(self, points=None):
"""
Plot the current state on the Bloch sphere using
qutip.
"""
if points is None:
# convert current state into density operator
rho = np.outer(self.state.H, self.state)
# get Bloch vector representation
points = self.get_bloch_vec(rho)
# Can only plot systems of dimension 2 at this time
assert len(
points
) == 3, "System dimension must be spin 1/2 for Bloch sphere plot"
# create instance of 3d plot
bloch = Bloch(figsize=[9, 9])
# add state
bloch.add_points(points)
bloch.add_vectors([0, 0, 1])
bloch.render(bloch.fig, bloch.axes)
bloch.fig.savefig("bloch.png", dpi=600, transparent=True)
bloch.show()
def animate_bloch(vectors, duration=0.1, save_all=False):
numberOfLoops = 1 #Enter '1' to apply only ONE mode [Excitation or Relaxation] or '2' to to apply only BOTH modes [Excitation and Relaxation] starting with the selected mode
if numberOfLoops == 1:
maxAngle = 2 * np.pi
elif numberOfLoops == 2:
maxAngle = 4 * np.pi
mode = 1 #Enter '0' to activate Excitation Mode or '1' to activate Relaxation Mode
omega = np.pi / 6 #Enter the angular frequency
z = 0
sqAngle = np.pi / 2
a = 5
vectorM = Bloch()
# vectorM.view = [90,90] #Activate this line to view magnetization’s trajectory on x-y plane
images = []
for t in np.arange(omega, maxAngle, 0.1):
if mode == 0:
z = np.pi / 2 * np.sin(t / (4))
if t == 2 * np.pi:
mode = 1
elif mode == 1:
z = np.pi / 2 * np.cos(t / (4))
if t == 2 * np.pi:
mode = 0
else:
pass
vectorM.clear()
vectorM.add_vectors([
np.sin(omega) * np.cos(t),
np.sin(omega) * np.sin(t),
np.cos(omega)
])
vectorM.add_vectors(
[np.sin(z) * np.cos(a * t),
np.sin(z) * np.sin(a * t),
np.cos(z)])
vectorM.add_vectors([
np.sin(sqAngle) * np.cos(t),
np.sin(sqAngle) * np.sin(t),
np.cos(sqAngle)
])
filename = 'temp_file.png'
vectorM.save(filename)
images.append(imageio.imread(filename))
imageio.mimsave('bloch_anim.gif', images, duration=duration)
#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Tue Jul 30 12:26:48 2019 @author: banano """ # from qutip import Bloch, Bloch3d b1 = Bloch() vec = [0,1,0] b1.add_vectors(vec) b1.vector_color = ['k'] b2 = Bloch() vec = [0,0,1] b2.add_vectors(vec) b2.vector_color = ['r'] b2.show() b1.show()
# %% -1-
# Bloch() erzeugt eine Bloch
# mit b verweisen wir spaeter auf diese
b = Bloch()
# b.show() zeigt die aktuelle Blochkugel an
b.show()
print('-1-')
input('Press ENTER to continue.'
) # Ansonst wird Fenster sofort wieder geschlossen bzw. ueberschrieben.
# %% -2-
# hinzufuegen eines Vektor
# x,y,z
v = [1, 0, 0] # dazu geben wir einen Vektor in die x-Richtung an
b.add_vectors(
v) # mit b.add_vectors wird der Vektor v der Blochkugel hinzugefuegt
b.show()
print('-2-')
input('Press ENTER to continue.')
# %% -3-
# Achsen koennen auch umbenannt werden
# dazu kann Latex-Code verwendet werden jedoch muss beachtet werden,
# dass fuer Latex-Code \ --> \\ verwendet werden sollte
b.xlabel = ["$\\left|45^\\circ \\right>$", "$\\left|-45^\\circ \\right>$"]
b.ylabel = ["$\\left|\\sigma^+\\right>$", "$\\left|\\sigma^- \\right>$"]
b.zlabel = ["$\\left|H\\right>$", "$\\left|V\\right>$"]
b.show()
print('-3-')
input('Press ENTER to continue.')
def bloch_plot2(self,
filename,
save=False,
vecList=[],
vecColour=[],
view=[190, 10],
points=None,
folder=False,
fig=False,
ax=False):
"""
Plot the current state on the Bloch sphere using
qutip.
"""
if points is None:
# convert current state into density operator
rho = np.outer(self.state.H, self.state)
# get Bloch vector representation
points = self.get_bloch_vec(rho)
# Can only plot systems of dimension 2 at this time
assert len(
points
) == 3, "System dimension must be spin 1/2 for Bloch sphere plot"
# create instance of 3d plot
if not fig or not ax:
bloch = Bloch(figsize=[9, 9], view=view)
else:
bloch = Bloch(fig=fig, axes=ax, view=view)
# add state
bloch.add_points(points)
# bloch.zlabel = [r'$\left|+z\right>$',r'$\left|-z\right>$']
bloch.zlabel = [r'$\ket{+_z}$', r'$\ket{-_z}$']
# bloch.ylabel = [r'$\ket{+_y}$',r'$\ket{-_y}$']
# bloch.ylabel = [r'$\ket{+_y}$',r'$\ket{-_y}$']
# print(vecList.shape)
# add vectors
if vecList.shape[1] == 3:
if len(vecColour) >= vecList.shape[0] and len(vecColour) > 0:
bloch.vector_color = vecColour
else:
bloch.vector_color = ['#CC6600', 'royalblue', 'r', 'm', 'g']
bloch.add_vectors(vecList)
# add field vector
# bloch.add_vectors([1,0,0.15])
# bloch.add_vectors([0,0,1])
# bloch.add_vectors([1,0,0])
# render bloch sphere
if not fig or not ax:
bloch.render()
else:
# bloch.render(fig = fig, axes = ax)
bloch.render(fig=fig)
# save output
if save is True:
if not folder:
folder = 'C:/Users/Boundsy/Desktop/Uni Work/PHS2360/Sim Results/'
print('Bloch plot saved to ' + str(folder))
path1 = folder + str(filename) + '.png'
path2 = folder + str(filename) + '.pdf'
bloch.fig.savefig(path1, dpi=800, transparent=True)
bloch.fig.savefig(path2, dpi=800, transparent=True)
# return axes for annotations
return bloch.fig, bloch.axes
def PlotBlochState(state):
bsph = Bloch()
bsph.add_vectors(StateToBloch(state))
return bsph.show()
#Input
x,y = map(complex,input("enter the state: ").split())
#Normalization
norm = np.sqrt(np.abs(x**2) + np.abs(y**2))
x /= norm
y /= norm
#Qubit allocation , define a state for the qubit,and measure it.
qubit = ME.allocate_qubit()
StatePreparation([x,y]) | qubit
Measure | qubit
read = int(qubit)
#Measuring output
ME.flush()
print(read)
#State vector to sphereical coordinates
phi = np.angle(y) - np.angle(x)
theta = 2 * np.arccos(np.abs(x))
vec = [np.sin(theta) * np.cos(phi), np.sin(theta) * np.sin(phi), np.cos(theta)]
#Visualization
b = Bloch()
b.add_vectors(vec)
b.show()
