def test_spectrum_espi_legacy():
"""
correlation: legacy spectrum from es and pi methods
"""
# use JC model
N = 4
wc = wa = 1.0 * 2 * np.pi
g = 0.1 * 2 * np.pi
kappa = 0.75
gamma = 0.25
n_th = 0.01
a = tensor(destroy(N), qeye(2))
sm = tensor(qeye(N), destroy(2))
H = wc * a.dag() * a + wa * sm.dag() * sm + \
g * (a.dag() * sm + a * sm.dag())
c_ops = [np.sqrt(kappa * (1 + n_th)) * a,
np.sqrt(kappa * n_th) * a.dag(),
np.sqrt(gamma) * sm]
wlist = 2 * np.pi * np.linspace(0.5, 1.5, 100)
with warnings.catch_warnings():
warnings.simplefilter("ignore")
spec1 = spectrum_ss(H, wlist, c_ops, a.dag(), a)
spec2 = spectrum_pi(H, wlist, c_ops, a.dag(), a)
assert_(max(abs(spec1 - spec2)) < 1e-3)
def test_spectrum_espi_legacy():
"""
correlation: legacy spectrum from es and pi methods
"""
# use JC model
N = 4
wc = wa = 1.0 * 2 * np.pi
g = 0.1 * 2 * np.pi
kappa = 0.75
gamma = 0.25
n_th = 0.01
a = tensor(destroy(N), qeye(2))
sm = tensor(qeye(N), destroy(2))
H = wc * a.dag() * a + wa * sm.dag() * sm + \
g * (a.dag() * sm + a * sm.dag())
c_ops = [
np.sqrt(kappa * (1 + n_th)) * a,
np.sqrt(kappa * n_th) * a.dag(),
np.sqrt(gamma) * sm
]
wlist = 2 * np.pi * np.linspace(0.5, 1.5, 100)
with warnings.catch_warnings():
warnings.simplefilter("ignore")
spec1 = spectrum_ss(H, wlist, c_ops, a.dag(), a)
spec2 = spectrum_pi(H, wlist, c_ops, a.dag(), a)
assert_(max(abs(spec1 - spec2)) < 1e-3)