In [1]:
%matplotlib inline
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from qutip import *
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rho = rand_dm(5)
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hinton(rho);
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theta = np.linspace(0, pi, 90)
phi = np.linspace(0, 2 * pi, 60)
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sphereplot(theta, phi, orbital(theta, phi, basis(3, 0)));
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fig = plt.figure(figsize=(16,4))
ax = fig.add_subplot(1, 3, 1, projection='3d')
sphereplot(theta, phi, orbital(theta, phi, basis(3, 0)), fig, ax);
ax = fig.add_subplot(1, 3, 2, projection='3d')
sphereplot(theta, phi, orbital(theta, phi, basis(3, 1)), fig, ax);
ax = fig.add_subplot(1, 3, 3, projection='3d')
sphereplot(theta, phi, orbital(theta, phi, basis(3, 2)), fig, ax);
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matrix_histogram(rho.full().real);
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matrix_histogram_complex(rho.full());
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H0 = tensor(sigmaz(), identity(2)) + tensor(identity(2), sigmaz())
Hint = 0.1 * tensor(sigmax(), sigmax())
plot_energy_levels([H0, Hint], figsize=(8,4));
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rho = (coherent(15, 1.5) + coherent(15, -1.5)).unit()
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plot_fock_distribution(rho);
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plot_wigner_fock_distribution(rho);
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plot_wigner(rho, figsize=(6,6));
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H = sigmaz() + 0.3 * sigmay()
e_ops = [sigmax(), sigmay(), sigmaz()]
times = np.linspace(0, 10, 100)
psi0 = (basis(2, 0) + basis(2, 1)).unit()
result = mesolve(H, psi0, times, [], e_ops)
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plot_expectation_values(result);
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b = Bloch()
b.add_vectors(expect(H.unit(), e_ops))
b.add_points(result.expect, meth='l')
b.make_sphere()
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j = 5
psi = spin_state(j, -j)
psi = spin_coherent(j, np.random.rand() * pi, np.random.rand() * 2 * pi)
rho = ket2dm(psi)
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theta = np.linspace(0, pi, 50)
phi = np.linspace(0, 2*pi, 50)
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Q, THETA, PHI = spin_q_function(psi, theta, phi)
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plot_spin_distribution_2d(Q, THETA, PHI);
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fig, ax = plot_spin_distribution_3d(Q, THETA, PHI);
ax.view_init(15, 30)
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fig = plt.figure(figsize=(14,6))
ax = fig.add_subplot(1, 2, 1)
f1, a1 = plot_spin_distribution_2d(Q, THETA, PHI, fig=fig, ax=ax)
ax = fig.add_subplot(1, 2, 2, projection='3d')
f2, a2 = plot_spin_distribution_3d(Q, THETA, PHI, fig=fig, ax=ax)
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W, THETA, PHI = spin_wigner(psi, theta, phi)
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fig = plt.figure(figsize=(14,6))
ax = fig.add_subplot(1, 2, 1)
f1, a1 = plot_spin_distribution_2d(W, THETA, PHI, fig=fig, ax=ax)
ax = fig.add_subplot(1, 2, 2, projection='3d')
f2, a2 = plot_spin_distribution_3d(W, THETA, PHI, fig=fig, ax=ax)
In [26]:
from qutip.ipynbtools import version_table
version_table()
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