本文整理汇总了Python中qutip.destroy函数的典型用法代码示例。如果您正苦于以下问题:Python destroy函数的具体用法?Python destroy怎么用?Python destroy使用的例子?那么恭喜您, 这里精选的函数代码示例或许可以为您提供帮助。
在下文中一共展示了destroy函数的15个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: compute
def compute(N, wc, wa, glist, use_rwa):
# Pre-compute operators for the hamiltonian
a = tensor(destroy(N), qeye(2))
sm = tensor(qeye(N), destroy(2))
nc = a.dag() * a
na = sm.dag() * sm
idx = 0
na_expt = zeros(shape(glist))
nc_expt = zeros(shape(glist))
for g in glist:
# recalculate the hamiltonian for each value of g
if use_rwa:
H = wc * nc + wa * na + g * (a.dag() * sm + a * sm.dag())
else:
H = wc * nc + wa * na + g * (a.dag() + a) * (sm + sm.dag())
# find the groundstate of the composite system
evals, ekets = H.eigenstates()
psi_gnd = ekets[0]
na_expt[idx] = expect(na, psi_gnd)
nc_expt[idx] = expect(nc, psi_gnd)
idx += 1
return nc_expt, na_expt, ket2dm(psi_gnd)
示例2: test_diagHamiltonian2
def test_diagHamiltonian2():
"""
Diagonalization of composite systems
"""
H1 = scipy.rand() * sigmax() + scipy.rand() * sigmay() +\
scipy.rand() * sigmaz()
H2 = scipy.rand() * sigmax() + scipy.rand() * sigmay() +\
scipy.rand() * sigmaz()
H = tensor(H1, H2)
evals, ekets = H.eigenstates()
for n in range(len(evals)):
# assert that max(H * ket - e * ket) is small
assert_equal(amax(
abs((H * ekets[n] - evals[n] * ekets[n]).full())) < 1e-10, True)
N1 = 10
N2 = 2
a1 = tensor(destroy(N1), qeye(N2))
a2 = tensor(qeye(N1), destroy(N2))
H = scipy.rand() * a1.dag() * a1 + scipy.rand() * a2.dag() * a2 + \
scipy.rand() * (a1 + a1.dag()) * (a2 + a2.dag())
evals, ekets = H.eigenstates()
for n in range(len(evals)):
# assert that max(H * ket - e * ket) is small
assert_equal(amax(
abs((H * ekets[n] - evals[n] * ekets[n]).full())) < 1e-10, True)
示例3: carrier_flop
def carrier_flop(rho0, W, eta, delta, theta, phi, c_op_list = [], return_op_list = []):
''' Return values of atom and motion populations during carrier Rabi flop
for rotation angles theta. Calls numerical solution of master equation.
@ var rho0: initial density matrix
@ var W: bare Rabi frequency
@ var eta: Lamb-Dicke parameter
@ var delta: detuning between atom and motion
@ var theta: list of Rabi rotation angles (i.e. theta, or g*time)
@ var phi: phase of the input laser pulse
@ var c_op_list: list of collapse operators for the master equation treatment
@ var return_op_list: list of population operators the values of which will be returned
returns: time, populations of motional mode and atom
'''
N = shape(rho0.data)[0]/2 # assume N Fock states and two atom states
a = tensor(destroy(N), qeye(2))
Wc = qeye(N)
Wc.data = csr_matrix( qeye(N).data.dot( np.diag(rabi_coupling(N,0,eta) ) ) )
sm = tensor( Wc, destroy(2))
# use the rotating wave approxiation
H = delta * a.dag() * a + \
(1./2.)* W * (sm.dag()*exp(1j*phi) + sm*exp(-1j*phi))
if hasattr(theta, '__len__'):
if len(theta)>1: # I need to be able to pass a list of length zero and not get an error
time = theta/W
else:
time = theta/W
output = mesolve(H, rho0, time, c_op_list, return_op_list)
return time, output
示例4: collapse_operators
def collapse_operators(N, n_th_a, gamma_motion, gamma_motion_phi, gamma_atom):
'''Collapse operators for the master equation of a single atom and a harmonic oscillator
@ var N: size of the harmonic oscillator Hilbert space
@ var n_th: temperature of the noise bath in quanta
@ var gamma_motion: heating rate of the motion
@ var gamma_motion_phi: dephasing rate of the motion
@ var gamma_atom: decay rate of the atom
returns: list of collapse operators for master equation solution of atom + harmonic oscillator
'''
a = tensor(destroy(N), qeye(2))
sm = tensor(qeye(N), destroy(2))
c_op_list = []
rate = gamma_motion * (1 + n_th_a)
if rate > 0.0:
c_op_list.append(sqrt(rate) * a)
rate = gamma_motion * n_th_a
if rate > 0.0:
c_op_list.append(sqrt(rate) * a.dag())
rate = gamma_motion_phi
if rate > 0.0:
c_op_list.append(sqrt(rate) * a.dag() * a)
rate = gamma_atom
if rate > 0.0:
c_op_list.append(sqrt(rate) * sm)
return c_op_list
示例5: testJCZeroTemperature
def testJCZeroTemperature():
"""
brmesolve: Jaynes-Cummings model, zero temperature
"""
N = 10
a = tensor(destroy(N), identity(2))
sm = tensor(identity(N), destroy(2))
psi0 = ket2dm(tensor(basis(N, 1), basis(2, 0)))
a_ops = [(a + a.dag())]
e_ops = [a.dag() * a, sm.dag() * sm]
w0 = 1.0 * 2 * np.pi
g = 0.05 * 2 * np.pi
kappa = 0.05
times = np.linspace(0, 2 * 2 * np.pi / g, 1000)
c_ops = [np.sqrt(kappa) * a]
H = w0 * a.dag() * a + w0 * sm.dag() * sm + \
g * (a + a.dag()) * (sm + sm.dag())
res_me = mesolve(H, psi0, times, c_ops, e_ops)
res_brme = brmesolve(H, psi0, times, a_ops, e_ops,
spectra_cb=[lambda w: kappa * (w >= 0)])
for idx, e in enumerate(e_ops):
diff = abs(res_me.expect[idx] - res_brme.expect[idx]).max()
assert_(diff < 5e-2) # accept 5% error
示例6: test_spectrum_espi_legacy
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)
示例7: test_spectrum_esfft
def test_spectrum_esfft():
"""
correlation: comparing spectrum from es and fft 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]
with warnings.catch_warnings():
warnings.simplefilter("ignore")
tlist = np.linspace(0, 100, 2500)
corr = correlation_ss(H, tlist, c_ops, a.dag(), a)
wlist1, spec1 = spectrum_correlation_fft(tlist, corr)
spec2 = spectrum_ss(H, wlist1, c_ops, a.dag(), a)
assert_(max(abs(spec1 - spec2)) < 1e-3)
示例8: test_spectrum_espi
def test_spectrum_espi():
"""
correlation: comparing 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 * pi * np.linspace(0.5, 1.5, 100)
spec1 = spectrum(H, wlist, c_ops, a.dag(), a, solver='es')
spec2 = spectrum(H, wlist, c_ops, a.dag(), a, solver='pi')
assert_(max(abs(spec1 - spec2)) < 1e-3)
示例9: rsb_flop
def rsb_flop(rho0, W, eta, delta, theta, phi, c_op_list = [], return_op_list = []):
''' Return values of atom and motion populations during red sideband Rabi flop
for rotation angles theta. Calls numerical solution of master equation for the
Jaynes-Cummings Hamiltonian.
@ var rho0: initial density matrix
@ var W: bare Rabi frequency
@ var delta: detuning between atom and motion
@ var theta: list of Rabi rotation angle (i.e. theta, or g*time)
@ var phi: phase of the input laser pulse
@ var c_op_list: list of collapse operators for the master equation treatment
@ var return_op_list: list of population operators the values of which will be returned
returns: time, populations of motional mode and atom
'''
N = shape(rho0.data)[0]/2 # assume N Fock states and two atom states
a = tensor(destroy(N), qeye(2))
sm = tensor( qeye(N), destroy(2))
Wrsb = destroy(N)
one_then_zero = ([float(x<1) for x in range(N)])
Wrsb.data = csr_matrix( destroy(N).data.dot( np.diag( rabi_coupling(N,-1,eta) / np.sqrt(one_then_zero+np.linspace(0,N-1,N)) ) ) )
Arsb = tensor(Wrsb, qeye(2))
# use the rotating wave approxiation
# Note that the regular a, a.dag() is used for the time evolution of the oscillator
# Arsb is the destruction operator including the state dependent coupling strength
H = delta * a.dag() * a + \
(1./2.) * W * (Arsb.dag() * sm * exp(1j*phi) + Arsb * sm.dag() * exp(-1j*phi))
if hasattr(theta, '__len__'):
if len(theta)>1: # I need to be able to pass a list of length zero and not get an error
time = theta/(eta*W)
else:
time = theta/(eta*W)
output = mesolve(H, rho0, time, c_op_list, return_op_list)
return time, output
示例10: test_enr_destory_full
def test_enr_destory_full():
"Excitation-number-restricted state-space: full state space"
a1, a2 = enr_destroy([4, 4], 4**2)
b1, b2 = tensor(destroy(4), identity(4)), tensor(identity(4), destroy(4))
assert_(a1 == b1)
assert_(a2 == b2)
示例11: __init__
def __init__(self):
N = 3
self.t1 = QobjEvo([qeye(N)*(1.+0.1j),[create(N)*(1.-0.1j),f]])
self.t2 = QobjEvo([destroy(N)*(1.-0.2j)])
self.t3 = QobjEvo([[destroy(N)*create(N)*(1.+0.2j),f]])
self.q1 = qeye(N)*(1.+0.3j)
self.q2 = destroy(N)*(1.-0.3j)
self.q3 = destroy(N)*create(N)*(1.+0.4j)
示例12: population_operators
def population_operators(N):
'''Population operators for the master equation
@ var N: size of the oscillator Hilbert space
returns: list of population operators for the harmonic oscillator and the atom
'''
a = tensor(destroy(N), qeye(2))
sm = tensor( qeye(N), destroy(2))
return [a.dag()*a, sm.dag()*sm]
示例13: test_destroy
def test_destroy():
"Destruction operator"
b4 = basis(5, 4)
d5 = destroy(5)
test1 = d5 * b4
assert_equal(np.allclose(test1.full(), 2.0 * basis(5, 3).full()), True)
d3 = destroy(3)
matrix3 = np.array([[0.00000000 + 0.j, 1.00000000 + 0.j, 0.00000000 + 0.j],
[0.00000000 + 0.j, 0.00000000 + 0.j, 1.41421356 + 0.j],
[0.00000000 + 0.j, 0.00000000 + 0.j, 0.00000000 + 0.j]])
assert_equal(np.allclose(matrix3, d3.full()), True)
示例14: full_hamiltonian
def full_hamiltonian(cav_dim, w_1, w_2, w_c, g_1, g_2):
"""Return a QObj denoting the full Hamiltonian including cavity
and two qubits"""
a = qt.destroy(cav_dim)
num = a.dag() * a
return (
g_1 * qt.tensor(qt.create(cav_dim), SMinus, I) +
g_1 * qt.tensor(qt.destroy(cav_dim), SPlus, I) +
g_2 * qt.tensor(qt.create(cav_dim), I, SMinus) +
g_2 * qt.tensor(qt.destroy(cav_dim), I, SPlus) +
w_c * qt.tensor(num, I, I) +
0.5 * w_1 * qt.tensor(qt.qeye(cav_dim), SZ, I) +
0.5 * w_2 * qt.tensor(qt.qeye(cav_dim), I, SZ))
示例15: test_smesolve_photocurrent
def test_smesolve_photocurrent():
"Stochastic: photocurrent_mesolve"
tol = 0.01
N = 4
gamma = 0.25
ntraj = 20
nsubsteps = 100
a = destroy(N)
H = [[a.dag() * a,f]]
psi0 = coherent(N, 0.5)
sc_ops = [np.sqrt(gamma) * a, np.sqrt(gamma) * a * 0.5]
e_ops = [a.dag() * a, a + a.dag(), (-1j)*(a - a.dag())]
times = np.linspace(0, 1.0, 21)
res_ref = mesolve(H, psi0, times, sc_ops, e_ops, args={"a":2})
res = photocurrent_mesolve(H, psi0, times, [], sc_ops, e_ops, args={"a":2},
ntraj=ntraj, nsubsteps=nsubsteps, store_measurement=True,
map_func=parallel_map)
assert_(all([np.mean(abs(res.expect[idx] - res_ref.expect[idx])) < tol
for idx in range(len(e_ops))]))
assert_(len(res.measurement) == ntraj)
assert_(all([m.shape == (len(times), len(sc_ops))
for m in res.measurement]))