def test_discrete_mean(self):
xpos, ephcoup = discrete_mean(spectral_density_Lorentzian, \
(eta, gamma, omega_v), 0.0, omega_c, 10)
print "discrete", xpos, ephcoup
dipole_abs = 1.0
nmols = 1
elocalex = 100000. * constant.cm2au
J = np.array([[0.]]) * constant.cm2au
omega_value = xpos * constant.cm2au
omega = [{0: x, 1: x} for x in omega_value]
D = [{
0: 0.0,
1: ephcoup[i] * np.sqrt(2. / omega_value[i])
} for i in range(len(ephcoup))]
nphs = len(xpos)
nlevels = [10] * nphs
phinfo = [list(a) for a in zip(omega, D, nlevels)]
mol = []
for imol in xrange(nmols):
mol_local = obj.Mol(elocalex, nphs, dipole_abs)
mol_local.create_ph(phinfo)
mol.append(mol_local)
nexciton = 0
procedure = [[20, 0.1], [10, 0], [1, 0]]
iMPS, iMPSdim, iMPSQN, HMPO, HMPOdim, HMPOQN, HMPOQNidx, HMPOQNtot, ephtable, pbond = \
MPSsolver.construct_MPS_MPO_2(mol, J, procedure[0][0], nexciton)
MPSsolver.optimization(iMPS, iMPSdim, iMPSQN, HMPO, HMPOdim, ephtable, pbond,\
nexciton, procedure, method="2site")
# if in the EX space, MPO minus E_e to reduce osillation
for ibra in xrange(pbond[0]):
HMPO[0][0, ibra, ibra, 0] -= elocalex
iMPS = [iMPS, iMPSQN, len(iMPS) - 1, 0]
QNargs = [ephtable, False]
HMPO = [HMPO, HMPOQN, HMPOQNidx, HMPOQNtot]
dipoleMPO, dipoleMPOdim = MPSsolver.construct_onsiteMPO(mol, pbond, \
"a^\dagger", dipole=True, QNargs=QNargs)
iMPS = mpslib.MPSdtype_convert(iMPS, QNargs=QNargs)
nsteps = 1000
dt = 30.
autocorr = tMPS.ZeroTCorr(iMPS, HMPO, dipoleMPO, nsteps, dt, ephtable, \
thresh=1.0e-4, cleanexciton=1-nexciton, algorithm=2, compress_method="svd", QNargs=QNargs)
with open("std_data/discretization/mean.npy", 'rb') as f:
mean_std = np.load(f)
self.assertTrue(np.allclose(autocorr, mean_std, rtol=1.e-3))
def test_ZeroTcorr(self, value):
print "data", value
nexciton = 0
procedure = [[1, 0], [1, 0], [1, 0]]
mol = construct_mol(*value[3])
iMPS, iMPSdim, iMPSQN, HMPO, HMPOdim, HMPOQN, HMPOQNidx, HMPOQNtot, ephtable, pbond = \
MPSsolver.construct_MPS_MPO_2(mol, J, procedure[0][0], nexciton)
MPSsolver.optimization(iMPS, iMPSdim, iMPSQN, HMPO, HMPOdim, ephtable, pbond,\
nexciton, procedure, method="2site")
# if in the EX space, MPO minus E_e to reduce osillation
for ibra in xrange(pbond[0]):
HMPO[0][0, ibra, ibra, 0] -= 2.28614053 / constant.au2ev
if value[2] != None:
iMPS = [iMPS, iMPSQN, len(iMPS) - 1, 0]
QNargs = [ephtable, False]
HMPO = [HMPO, HMPOQN, HMPOQNidx, HMPOQNtot]
else:
QNargs = None
dipoleMPO, dipoleMPOdim = MPSsolver.construct_onsiteMPO(mol,
pbond,
"a^\dagger",
dipole=True,
QNargs=QNargs)
iMPS = mpslib.MPSdtype_convert(iMPS, QNargs=QNargs)
nsteps = 100
dt = 30.0
autocorr = tMPS.ZeroTCorr(iMPS,
HMPO,
dipoleMPO,
nsteps,
dt,
ephtable,
thresh=1.0e-3,
cleanexciton=1 - nexciton,
algorithm=value[0],
compress_method=value[1],
QNargs=QNargs)
autocorr = np.array(autocorr)
with open(
"std_data/tMPS/ZeroTabs_" + str(value[0]) + str(value[1]) +
".npy", 'rb') as f:
ZeroTabs_std = np.load(f)
self.assertTrue(np.allclose(autocorr, ZeroTabs_std, rtol=value[4]))
def test_ZeroTcorr(self, value):
nexciton = 0
procedure = [[20, 0.5], [10, 0.1], [5, 0], [1, 0]]
mol = construct_mol(*value[0])
Chain = chainmap.Chain_Map_discrete(mol)
mol = chainmap.Chain_Mol(Chain, mol)
iMPS, iMPSdim, iMPSQN, HMPO, HMPOdim, HMPOQN, HMPOQNidx, HMPOQNtot, ephtable, pbond = \
MPSsolver.construct_MPS_MPO_2(mol, J, procedure[0][0], nexciton,\
rep="chain")
MPSsolver.optimization(iMPS, iMPSdim, iMPSQN, HMPO, HMPOdim, ephtable, pbond,\
nexciton, procedure, method="2site")
# if in the EX space, MPO minus E_e to reduce osillation
for ibra in xrange(pbond[0]):
HMPO[0][0, ibra, ibra, 0] -= 2.28614053 / constant.au2ev
iMPS = [iMPS, iMPSQN, len(iMPS) - 1, 0]
QNargs = [ephtable, False]
HMPO = [HMPO, HMPOQN, HMPOQNidx, HMPOQNtot]
dipoleMPO, dipoleMPOdim = MPSsolver.construct_onsiteMPO(mol,
pbond,
"a^\dagger",
dipole=True,
QNargs=QNargs)
iMPS = mpslib.MPSdtype_convert(iMPS, QNargs=QNargs)
nsteps = 100
dt = 10.0
autocorr = tMPS.ZeroTCorr(iMPS,
HMPO,
dipoleMPO,
nsteps,
dt,
ephtable,
thresh=1.0e-3,
cleanexciton=1 - nexciton,
algorithm=2,
compress_method="svd",
QNargs=QNargs)
autocorr = np.array(autocorr)
with open("std_data/quasiboson/0Tabs_std.npy", 'rb') as f:
ZeroTabs_std = np.load(f)
self.assertTrue(np.allclose(autocorr, ZeroTabs_std, rtol=value[1]))
def test_ZeroTcorr_TDVP(self, value):
nexciton = 0
procedure = [[50, 0], [50, 0], [50, 0]]
iMPS, iMPSdim, iMPSQN, HMPO, HMPOdim, HMPOQN, HMPOQNidx, HMPOQNtot, ephtable, pbond = \
MPSsolver.construct_MPS_MPO_2(mol, J, procedure[0][0], nexciton)
MPSsolver.optimization(iMPS, iMPSdim, iMPSQN, HMPO, HMPOdim, ephtable, pbond,\
nexciton, procedure, method="2site")
# if in the EX space, MPO minus E_e to reduce osillation
for ibra in xrange(pbond[0]):
HMPO[0][0, ibra, ibra, 0] -= 2.28614053 / constant.au2ev
dipoleMPO, dipoleMPOdim = MPSsolver.construct_onsiteMPO(mol,
pbond,
"a^\dagger",
dipole=True)
iMPS = mpslib.MPSdtype_convert(iMPS)
nsteps = 200
dt = value[2]
for f in glob.glob("TDVP_PS*.npy"):
os.remove(f)
autocorr = tMPS.ZeroTCorr(iMPS,
HMPO,
dipoleMPO,
nsteps,
dt,
ephtable,
thresh=1.0e-7,
cleanexciton=1 - nexciton,
algorithm=value[1],
compress_method="variational",
scheme=value[0])
with open("std_data/tMPS/ZeroTabs_" + value[0] + ".npy", 'rb') as f:
ZeroTabs_std = np.load(f)
self.assertTrue(
np.allclose(autocorr, ZeroTabs_std[:len(autocorr)], rtol=value[3]))
def test_ZeroTcorr_MPOscheme3(self, value):
print "data", value
J = np.array([[0.0, -0.1, 0.0], [-0.1, 0.0, -0.3], [0.0, -0.3, 0.0]
]) / constant.au2ev
nexciton = 0
procedure = [[1, 0], [1, 0], [1, 0]]
mol = construct_mol(*value[3])
iMPS, iMPSdim, iMPSQN, HMPO, HMPOdim, HMPOQN, HMPOQNidx, HMPOQNtot, ephtable, pbond = \
MPSsolver.construct_MPS_MPO_2(mol, J, procedure[0][0], nexciton, MPOscheme=2)
MPSsolver.optimization(iMPS, iMPSdim, iMPSQN, HMPO, HMPOdim, ephtable, pbond,\
nexciton, procedure, method="2site")
# if in the EX space, MPO minus E_e to reduce osillation
for ibra in xrange(pbond[0]):
HMPO[0][0, ibra, ibra, 0] -= 2.28614053 / constant.au2ev
if value[2] != None:
iMPS = [iMPS, iMPSQN, len(iMPS) - 1, 0]
QNargs = [ephtable, False]
HMPO = [HMPO, HMPOQN, HMPOQNidx, HMPOQNtot]
else:
QNargs = None
dipoleMPO, dipoleMPOdim = MPSsolver.construct_onsiteMPO(mol,
pbond,
"a^\dagger",
dipole=True,
QNargs=QNargs)
iMPS = mpslib.MPSdtype_convert(iMPS, QNargs=QNargs)
nsteps = 50
dt = 30.0
autocorr = tMPS.ZeroTCorr(iMPS,
HMPO,
dipoleMPO,
nsteps,
dt,
ephtable,
thresh=1.0e-4,
cleanexciton=1 - nexciton,
algorithm=value[0],
compress_method=value[1],
QNargs=QNargs)
autocorr = np.array(autocorr)
# scheme3
iMPS3, iMPSdim3, iMPSQN3, HMPO3, HMPOdim3, HMPOQN3, HMPOQNidx3, HMPOQNtot3, ephtable3, pbond3 = \
MPSsolver.construct_MPS_MPO_2(mol, J, procedure[0][0], nexciton, MPOscheme=3)
MPSsolver.optimization(iMPS3, iMPSdim3, iMPSQN3, HMPO3, HMPOdim3, ephtable3, pbond3,\
nexciton, procedure, method="2site")
# if in the EX space, MPO minus E_e to reduce osillation
for ibra in xrange(pbond3[0]):
HMPO3[0][0, ibra, ibra, 0] -= 2.28614053 / constant.au2ev
if value[2] != None:
iMPS3 = [iMPS3, iMPSQN3, len(iMPS3) - 1, 0]
QNargs3 = [ephtable3, False]
HMPO3 = [HMPO3, HMPOQN3, HMPOQNidx3, HMPOQNtot3]
else:
QNargs3 = None
dipoleMPO, dipoleMPOdim = MPSsolver.construct_onsiteMPO(mol,
pbond,
"a^\dagger",
dipole=True,
QNargs=QNargs3)
iMPS3 = mpslib.MPSdtype_convert(iMPS3, QNargs=QNargs)
nsteps = 50
dt = 30.0
autocorr3 = tMPS.ZeroTCorr(iMPS3, HMPO3, dipoleMPO, nsteps, dt, ephtable3,\
thresh=1.0e-4, cleanexciton=1-nexciton, algorithm=value[0],
compress_method=value[1], QNargs=QNargs3)
autocorr3 = np.array(autocorr3)
self.assertTrue(np.allclose(autocorr, autocorr3, rtol=value[4]))