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)
@unittest.skipIf(_version2int(Cython.__version__) < _version2int('0.14') or
Cython_found == 0, 'Cython not found or version too low.')
def test_str_list_td_corr():
"""
correlation: comparing TLS emission correlations (str-list td format)
"""
# calculate emission zero-delay second order correlation, g2(0), for TLS
# with following parameters:
# gamma = 1, omega = 2, tp = 0.5
# Then: g2(0)~0.57
sm = destroy(2)
args = {"t_off": 1, "tp": 0.5}
H = [[2 * (sm+sm.dag()), "exp(-(t-t_off)**2 / (2*tp**2))"]]
tlist = np.linspace(0, 5, 50)
corr = correlation_3op_2t(H, fock(2, 0), tlist, tlist, [sm],
#
# Copyright (C) 2011 and later, Paul D. Nation & Robert J. Johansson
#
###########################################################################
from qutip import *
from qutip import _version2int
from qutip.sparse import *
from numpy import allclose, isreal, iscomplex
from numpy.testing import assert_equal, run_module_suite
import scipy
import unittest
@unittest.skipIf(_version2int(scipy.__version__) < _version2int('0.10'),
'Known to fail on SciPy ' + scipy.__version__)
def test_SparseHermValsVecs():
"""
Sparse eigs Hermitian
"""
# check using number operator
N = num(10)
spvals, spvecs = N.eigenstates(sparse=True)
for k in range(10):
# check that eigvals are in proper order
assert_equal(abs(spvals[k] - k) <= 1e-13, True)
# check that eigenvectors are right and in right order
assert_equal(abs(expect(N, spvecs[k]) - spvals[k]) < 5e-14, True)
import unittest
import warnings
from qutip import (correlation, destroy, coherent_dm, correlation_2op_2t,
fock, correlation_2op_1t, tensor, qeye, spectrum_ss,
spectrum_pi, correlation_ss, spectrum_correlation_fft,
spectrum, correlation_3op_2t, mesolve, Options,
Cubic_Spline)
# find Cython if it exists
try:
import Cython
except:
Cython_OK = False
else:
Cython_OK = _version2int(Cython.__version__) >= _version2int('0.14')
def test_compare_solvers_coherent_state_legacy():
"""
correlation: legacy me and es for oscillator in coherent initial state
"""
N = 20
a = destroy(N)
H = a.dag() * a
G1 = 0.75
n_th = 2.00
c_ops = [np.sqrt(G1 * (1 + n_th)) * a, np.sqrt(G1 * n_th) * a.dag()]
rho0 = coherent_dm(N, np.sqrt(4.0))
taulist = np.linspace(0, 5.0, 100)
# THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
###############################################################################
import scipy
import numpy as np
from numpy.testing import assert_equal, run_module_suite
import unittest
from qutip import num, rand_herm, expect, rand_unitary
from qutip import _version2int
@unittest.skipIf(
_version2int(scipy.__version__) < _version2int('0.10'),
'Known to fail on SciPy ' + scipy.__version__)
def test_SparseHermValsVecs():
"""
Sparse eigs Hermitian
"""
# check using number operator
N = num(10)
spvals, spvecs = N.eigenstates(sparse=True)
for k in range(10):
# check that eigvals are in proper order
assert_equal(abs(spvals[k] - k) <= 1e-13, True)
# check that eigenvectors are right and in right order
assert_equal(abs(expect(N, spvecs[k]) - spvals[k]) < 5e-14, True)
g * (a.dag() * sm + a * sm.dag())
c_ops = [
sqrt(kappa * (1 + n_th)) * a,
sqrt(kappa * n_th) * a.dag(),
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)
@unittest.skipIf(
_version2int(Cython.__version__) < _version2int('0.14')
or Cython_found == 0, 'Cython not found or version too low.')
def test_str_list_td_corr():
"""
correlation: comparing TLS emission correlations (str-list td format)
"""
# calculate emission zero-delay second order correlation, g2(0), for TLS
# with following parameters:
# gamma = 1, omega = 2, tp = 0.5
# Then: g2(0)~0.57
sm = destroy(2)
args = {"t_off": 1, "tp": 0.5}
H = [[2 * (sm + sm.dag()), "exp(-(t-t_off)**2 / (2*tp**2))"]]
tlist = linspace(0, 5, 50)
corr = correlation_3op_2t(H,
# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
###############################################################################
import numpy as np
from numpy.testing import assert_, run_module_suite, assert_allclose
import unittest
from qutip import *
from qutip import _version2int
try:
import Cython
except:
Cython_OK = False
else:
Cython_OK = _version2int(Cython.__version__) >= _version2int('0.14')
@unittest.skipIf(not Cython_OK, 'Cython not found or version too low.')
def test_td_brmesolve_basic():
"""
td_brmesolve: passes all brmesolve tests
"""
# Test #1
delta = 0.0 * 2 * np.pi
epsilon = 0.5 * 2 * np.pi
gamma = 0.25
times = np.linspace(0, 10, 100)
H = delta / 2 * sigmax() + epsilon / 2 * sigmaz()
psi0 = (2 * basis(2, 0) + basis(2, 1)).unit()
# LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
# DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
# THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
###############################################################################
import pytest
import numpy as np
import qutip
try:
import Cython
except ImportError:
Cython_OK = False
else:
cython_version = qutip._version2int(Cython.__version__)
Cython_OK = cython_version >= qutip._version2int('0.14')
pytestmark = pytest.mark.skipif(not Cython_OK,
reason="Cython not found, or version too low.",
allow_module_level=True)
def pauli_spin_operators():
return [qutip.sigmax(), qutip.sigmay(), qutip.sigmaz()]
_simple_qubit_gamma = 0.25
_m_c_op = np.sqrt(_simple_qubit_gamma) * qutip.sigmam()
_z_c_op = np.sqrt(_simple_qubit_gamma) * qutip.sigmaz()
_x_a_op = [qutip.sigmax(), '{0} * (w >= 0)'.format(_simple_qubit_gamma)]
N = 10 # number of basis states to consider
a = destroy(N)
H = a.dag() * a
psi0 = basis(N, 9) # initial state
kappa = 0.2 # coupling to oscillator
c_op_list = [[a, sqrt_kappa]]
tlist = np.linspace(0, 10, 100)
mcdata = mcsolve(H, psi0, tlist, c_op_list, [a.dag() * a], ntraj=ntraj)
expt = mcdata.expect[0]
actual_answer = 9.0 * np.exp(-kappa * tlist)
avg_diff = np.mean(abs(actual_answer - expt) / actual_answer)
assert_equal(avg_diff < mc_error, True)
@unittest.skipIf(
_version2int(Cython.__version__) < _version2int("0.14") or Cython_found == 0, "Cython not found or version too low."
)
def test_MCSimpleConstStr():
"Monte-carlo: Collapse terms constant (str format)"
N = 10 # number of basis states to consider
a = destroy(N)
H = a.dag() * a
psi0 = basis(N, 9) # initial state
kappa = 0.2 # coupling to oscillator
c_op_list = [[a, "sqrt(k)"]]
args = {"k": kappa}
tlist = np.linspace(0, 10, 100)
mcdata = mcsolve(H, psi0, tlist, c_op_list, [a.dag() * a], args=args, ntraj=ntraj)
expt = mcdata.expect[0]
actual_answer = 9.0 * np.exp(-kappa * tlist)
avg_diff = np.mean(abs(actual_answer - expt) / actual_answer)
"Monte-carlo: Collapse terms constant (func format)"
N = 10 # number of basis states to consider
a = destroy(N)
H = a.dag() * a
psi0 = basis(N, 9) # initial state
kappa = 0.2 # coupling to oscillator
c_op_list = [[a, sqrt_kappa]]
tlist = linspace(0, 10, 100)
mcdata = mcsolve(H, psi0, tlist, c_op_list, [a.dag() * a])
expt = mcdata.expect[0]
actual_answer = 9.0 * exp(-kappa * tlist)
avg_diff = mean(abs(actual_answer - expt) / actual_answer)
assert_equal(avg_diff < mc_error, True)
@unittest.skipIf(_version2int(Cython.__version__) < _version2int('0.14') or
Cython_found == 0, 'Cython not found or version too low.')
def test_MCSimpleConstStr():
"Monte-carlo: Collapse terms constant (str format)"
N = 10 # number of basis states to consider
a = destroy(N)
H = a.dag() * a
psi0 = basis(N, 9) # initial state
kappa = 0.2 # coupling to oscillator
c_op_list = [[a, 'sqrt(k)']]
args = {'k': kappa}
tlist = linspace(0, 10, 100)
mcdata = mcsolve(H, psi0, tlist, c_op_list, [a.dag() * a], args=args)
expt = mcdata.expect[0]
actual_answer = 9.0 * exp(-kappa * tlist)
avg_diff = mean(abs(actual_answer - expt) / actual_answer)
# DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
# THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
###############################################################################
import scipy
import numpy as np
from numpy.testing import assert_equal, run_module_suite, assert_
import unittest
from qutip import num, rand_herm, expect, rand_unitary
from qutip import _version2int
@unittest.skipIf(_version2int(scipy.__version__) < _version2int('0.10'),
'Known to fail on SciPy ' + scipy.__version__)
def test_SparseHermValsVecs():
"""
Sparse eigs Hermitian
"""
# check using number operator
N = num(10)
spvals, spvecs = N.eigenstates(sparse=True)
for k in range(10):
# check that eigvals are in proper order
assert_equal(abs(spvals[k] - k) <= 1e-13, True)
# check that eigenvectors are right and in right order
assert_equal(abs(expect(N, spvecs[k]) - spvals[k]) < 5e-14, True)
