Author: J. R. Johansson (robert@riken.jp), https://jrjohansson.github.io/
This lecture series was developed by J.R. Johannson. The original lecture notebooks are available here.
This is a slightly modified version of the lectures, to work with the current release of QuTiP. You can find these lectures as a part of the qutip-tutorials repository. This lecture and other tutorial notebooks are indexed at the QuTiP Tutorial webpage.
import matplotlib.pyplot as plt
import numpy as np
from qutip import (about, correlation_2op_1t, correlation_4op_1t, destroy,
expect, identity, liouvillian,
plot_wigner_fock_distribution, spectrum_correlation_fft,
spost, spre, steadystate, tensor)
%matplotlib inline
In Chapter 12 (Cascaded quantum systems) in Quantum Noise by Gardiner and Zoller (Springer, 3rd edition), a few examples of nonclassically driven atoms are given. In this notebook we solve for the dynamics of those systems using QuTiP.
The master equation for a two-level atom driven by a squeezed light can be written as (Ch. 12.2.2 in Quantum Noise)
$$ \dot\rho = -i[H, \rho] + \kappa\mathcal{D}[a]\rho + \gamma\mathcal{D}[\sigma_-]\rho -\sqrt{\eta\kappa\gamma}\{[\sigma_+, a\rho] + [\rho a^\dagger, \sigma_-]\} $$where
$$ H = i\frac{1}{2}(E {a^\dagger}^2 - E^* a^2) $$and
$$ \mathcal{D}[a]\rho = a \rho a^\dagger - \frac{1}{2}\rho a^\dagger a - \frac{1}{2}a^\dagger a\rho $$N = 10
gamma = 1
eta = 0.9
def solve(N, gamma, kappa, eta):
E = kappa * 0.25
# create operators
a = tensor(destroy(N), identity(2))
sm = tensor(identity(N), destroy(2))
# Hamiltonian
H = 0.5j * (E * a.dag() ** 2 - np.conjugate(E) * a**2)
# master equation superoperators
L0 = liouvillian(H, [np.sqrt(kappa) * a, np.sqrt(gamma) * sm])
L1 = -np.sqrt(kappa * gamma * eta) * (
spre(sm.dag() * a)
- spre(a) * spost(sm.dag())
+ spost(a.dag() * sm)
- spre(sm) * spost(a.dag())
)
L = L0 + L1
# steady state
rhoss = steadystate(L)
# correlation function and spectrum
taulist = np.linspace(0, 500, 2500)
c = correlation_2op_1t(L, rhoss, taulist, [], sm.dag(), sm)
w, S = spectrum_correlation_fft(taulist, c)
ww = np.hstack([np.fliplr(-np.array([w])).squeeze(), w])
SS = np.hstack([np.fliplr(np.array([S])).squeeze(), S])
return rhoss, ww, SS
rhoss2, w2, S2 = solve(N, gamma, 2, eta)
rhoss4, w4, S4 = solve(N, gamma, 4, eta)
rhoss8, w8, S8 = solve(N, gamma, 8, eta)
plot_wigner_fock_distribution(rhoss2.ptrace(0))
plot_wigner_fock_distribution(rhoss4.ptrace(0))
plot_wigner_fock_distribution(rhoss8.ptrace(0));
fig, ax = plt.subplots()
ax.plot(w2, S2 / S2.max(), label=r"$\kappa = 2$")
ax.plot(w4, S4 / S4.max(), label=r"$\kappa = 4$")
ax.plot(w8, S8 / S8.max(), label=r"$\kappa = 8$")
ax.plot(w8, 0.25 / ((0.5 * gamma) ** 2 + w8**2), "k:", label=r"Lorentian")
ax.legend()
ax.set_ylabel(r"Flouresence spectrum", fontsize=16)
ax.set_xlabel(r"$\omega$", fontsize=18)
ax.set_xlim(-2, 2);
Fig. 12.4 in Quantum Noise.
The master equation given in Sec. 12.3.1 in Quantum Noise, for two coupled atoms where the first atom (source atom) is irradiated with coherent light, and the second atom is irradiated by the antibunched light emitted from the source atom, is:
$$ \dot\rho = -i[H, \rho] + \gamma_1\mathcal{D}[\sigma^-_{1}]\rho + \gamma_2\mathcal{D}[\sigma^-_{2}]\rho -\sqrt{(1-\epsilon_1)(1-\epsilon_2)\gamma_1\gamma_2} ([\sigma_2^+, \sigma_1^-\rho] + [\rho\sigma_1^+, \sigma_2^-]) $$where
$$ H = -i\sqrt{\epsilon_1\gamma_1}(E\sigma_1^+ - E^*\sigma_1^-) $$e1 = 0.5
e2 = 0.5
gamma1 = 2
gamma2 = 2
E = 2 / np.sqrt(e1 * gamma1)
sm1 = tensor(destroy(2), identity(2))
sp1 = sm1.dag()
sm2 = tensor(identity(2), destroy(2))
sp2 = sm2.dag()
H = -1j * np.sqrt(e1 * gamma1) * (E * sp1 - np.conjugate(E) * sm1)
L0 = liouvillian(H, [np.sqrt(gamma1) * sm1, np.sqrt(gamma2) * sm2])
L1 = -np.sqrt((1 - e1) * (1 - e2) * gamma1 * gamma2) * (
spre(sp2 * sm1) - spre(sm1) * spost(sp2) +
spost(sp1 * sm2) - spre(sm2) * spost(sp1)
)
L = L0 + L1
# steady state
rhoss = steadystate(L)
# correlation function and spectrum
taulist = np.linspace(0, 4, 250)
G2_11 = correlation_4op_1t(L, rhoss, taulist, [], sp1, sp1, sm1, sm1)
g2_11 = G2_11 / (expect(sp1 * sm1, rhoss) * expect(sp1 * sm1, rhoss))
/home/runner/work/qutip-tutorials/qutip-tutorials/qutip/qutip/correlation.py:791: FutureWarning: correlation_4op_1t() now legacy, please use correlation_3op_1t() warn("correlation_4op_1t() now legacy, please use correlation_3op_1t()",
G2_22 = correlation_4op_1t(L, rhoss, taulist, [], sp2, sp2, sm2, sm2)
g2_22 = G2_22 / (expect(sp2 * sm2, rhoss) * expect(sp2 * sm2, rhoss))
G2_12 = correlation_4op_1t(L, rhoss, taulist, [], sp2, sp1, sm1, sm2)
g2_12 = G2_12 / (expect(sp1 * sm1, rhoss) * expect(sp2 * sm2, rhoss))
G2_21 = correlation_4op_1t(L, rhoss, taulist, [], sp1, sp2, sm2, sm1)
g2_21 = G2_21 / (expect(sp2 * sm2, rhoss) * expect(sp1 * sm1, rhoss))
fig, ax = plt.subplots()
ax.plot(taulist, np.real(g2_11), label=r"$g^{(2)}_{11}(\tau)$")
ax.plot(taulist, np.real(g2_22), label=r"$g^{(2)}_{22}(\tau)$")
ax.plot(taulist, np.real(g2_12), label=r"$g^{(2)}_{12}(\tau)$")
ax.plot(taulist, np.real(g2_21), label=r"$g^{(2)}_{21}(\tau)$")
ax.legend(loc=4)
ax.set_xlabel(r"$\tau$");
Fig. 12.6 in Quantum Noise.
When the source atom is irradiated with incoherent light, the master equation becomes (Sec. 12.3.2 in Quantum Noise)
$$ \dot\rho = \gamma_1\mathcal{D}[\sigma^-_{1}]\rho + \gamma_2\mathcal{D}[\sigma^-_{2}]\rho + \kappa(\bar{N} + 1)\mathcal{D}[a]\rho + \kappa\bar{N}\mathcal{D}[a^\dagger]\rho -\sqrt{2\kappa\eta_1\gamma_1} ([\sigma_1^+, a\rho] + [\rho a^\dagger, \sigma_1^-]) -\sqrt{\eta_2\gamma1\gamma_2} ([\sigma_2^+, \sigma_1^-\rho] + [\rho\sigma_1^+, \sigma_2^-]) $$N = 10
e1 = 0.5
e2 = 0.5
ek = 0.5
n_th = 1
kappa = 0.1
gamma1 = 1
gamma2 = 1
E = 0.025
taulist = np.linspace(0, 5, 250)
a = tensor(destroy(N), identity(2), identity(2))
sm1 = tensor(identity(N), destroy(2), identity(2))
sp1 = sm1.dag()
sm2 = tensor(identity(N), identity(2), destroy(2))
sp2 = sm2.dag()
def solve(ek, e1, e2, gamma1, gamma2, kappa, n_th, E):
eta1 = (1 - ek) * e1
eta2 = (1 - e1) * (1 - e2)
H = 1j * E * (a - a.dag())
L0 = liouvillian(
H,
[
np.sqrt(kappa * (1 + n_th)) * a,
np.sqrt(kappa * n_th) * a.dag(),
np.sqrt(gamma1) * sm1,
np.sqrt(gamma2) * sm2,
],
)
L1 = -np.sqrt(2 * kappa * eta1 * gamma1) * (
spre(sp1 * a)
- spre(a) * spost(sp1)
+ spost(a.dag() * sm1)
- spre(sm1) * spost(a.dag())
) + -np.sqrt(eta2 * gamma1 * gamma2) * (
spre(sp2 * sm1)
- spre(sm1) * spost(sp2)
+ spost(sp1 * sm2)
- spre(sm2) * spost(sp1)
)
L = L0 + L1
rhoss = steadystate(L)
G2_11 = correlation_4op_1t(L, rhoss, taulist, [], sp1, sp1, sm1, sm1)
g2_11 = G2_11 / (expect(sp1 * sm1, rhoss) * expect(sp1 * sm1, rhoss))
G2_22 = correlation_4op_1t(L, rhoss, taulist, [], sp2, sp2, sm2, sm2)
g2_22 = G2_22 / (expect(sp2 * sm2, rhoss) * expect(sp2 * sm2, rhoss))
G2_12 = correlation_4op_1t(L, rhoss, taulist, [], sp2, sp1, sm1, sm2)
g2_12 = G2_12 / (expect(sp1 * sm1, rhoss) * expect(sp2 * sm2, rhoss))
G2_21 = correlation_4op_1t(L, rhoss, taulist, [], sp1, sp2, sm2, sm1)
g2_21 = G2_21 / (expect(sp2 * sm2, rhoss) * expect(sp1 * sm1, rhoss))
return rhoss, g2_11, g2_12, g2_21, g2_22
# thermal
rhoss_t, g2_11_t, g2_12_t, g2_21_t, g2_22_t = solve(
ek, e1, e2, gamma1, gamma2, kappa, n_th, 0.0
)
# visualize the cavity state
plot_wigner_fock_distribution(rhoss_t.ptrace(0));
fig, ax = plt.subplots(figsize=(8, 4))
ax.plot(taulist, np.real(g2_11_t), label=r"$g^{(2)}_{11}(\tau)$")
ax.plot(taulist, np.real(g2_22_t), label=r"$g^{(2)}_{22}(\tau)$")
ax.plot(taulist, np.real(g2_12_t), label=r"$g^{(2)}_{12}(\tau)$")
ax.plot(taulist, np.real(g2_21_t), label=r"$g^{(2)}_{21}(\tau)$")
ax.legend(loc=4)
ax.set_xlabel(r"$\tau$", fontsize=16);
Similar to Fig. 12.8 in Quantum Noise, although not exactly because of different parameters.
about()
QuTiP: Quantum Toolbox in Python ================================ Copyright (c) QuTiP team 2011 and later. Current admin team: Alexander Pitchford, Nathan Shammah, Shahnawaz Ahmed, Neill Lambert, Eric Giguère, Boxi Li, Jake Lishman, Simon Cross and Asier Galicia. Board members: Daniel Burgarth, Robert Johansson, Anton F. Kockum, Franco Nori and Will Zeng. Original developers: R. J. Johansson & P. D. Nation. Previous lead developers: Chris Granade & A. Grimsmo. Currently developed through wide collaboration. See https://github.com/qutip for details. QuTiP Version: 4.7.1 Numpy Version: 1.22.4 Scipy Version: 1.8.1 Cython Version: 0.29.33 Matplotlib Version: 3.5.2 Python Version: 3.10.4 Number of CPUs: 2 BLAS Info: Generic OPENMP Installed: False INTEL MKL Ext: False Platform Info: Linux (x86_64) Installation path: /home/runner/work/qutip-tutorials/qutip-tutorials/qutip/qutip ================================================================================ Please cite QuTiP in your publication. ================================================================================ For your convenience a bibtex reference can be easily generated using `qutip.cite()`