def test_FiniteT_spectra_emi(self, value):
print "data", value
nexciton = 1
procedure = [[10, 0.4], [20, 0.2], [30, 0.1], [40, 0], [40, 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)
# 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:
QNargs = [ephtable, False]
HMPO = [HMPO, HMPOQN, HMPOQNidx, HMPOQNtot]
else:
QNargs = None
dipoleMPO, dipoleMPOdim = MPSsolver.construct_onsiteMPO(mol,
pbond,
"a",
dipole=True,
QNargs=QNargs)
nsteps = 30
dt = 30.0
EXMPO, EXMPOdim = tMPS.Max_Entangled_EX_MPO(mol,
pbond,
norm=True,
QNargs=QNargs)
EXMPO = mpslib.MPSdtype_convert(EXMPO, QNargs=QNargs)
insteps = 50
autocorr = tMPS.FiniteT_spectra("emi",
mol,
pbond,
EXMPO,
HMPO,
dipoleMPO,
nsteps,
dt,
ephtable,
insteps,
thresh=1.0e-3,
temperature=298,
algorithm=value[0],
compress_method=value[1],
QNargs=QNargs)
autocorr = np.array(autocorr)
with open(
"std_data/tMPS/TTemi_" + str(value[0]) + str(value[1]) +
".npy", 'rb') as f:
TTemi_std = np.load(f)
self.assertTrue(
np.allclose(autocorr, TTemi_std[0:nsteps], rtol=value[4]))
def test_FiniteT_spectra_emi(self, value):
nexciton = 1
procedure = [[10, 0.4], [20, 0.2], [30, 0.1], [40, 0], [40, 0]]
iMPS, iMPSdim, iMPSQN, HMPO, HMPOdim, HMPOQN, HMPOQNidx, HMPOQNtot, ephtable, pbond = \
MPSsolver.construct_MPS_MPO_2(mol, J, procedure[0][0], nexciton)
# 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",
dipole=True)
nsteps = value[1]
dt = value[2]
EXMPO, EXMPOdim = tMPS.Max_Entangled_EX_MPO(mol, pbond, norm=True)
EXMPO = mpslib.MPSdtype_convert(EXMPO)
for f in glob.glob("TDVP_PS*.npy"):
os.remove(f)
insteps = 50
autocorr = tMPS.FiniteT_spectra("emi",
mol,
pbond,
EXMPO,
HMPO,
dipoleMPO,
nsteps,
dt,
ephtable,
insteps,
thresh=1.0e-3,
temperature=298,
compress_method="variational",
scheme=value[0])
with open("std_data/tMPS/TTemi_2svd" + value[4] + ".npy", 'rb') as f:
TTemi_std = np.load(f)
self.assertTrue(
np.allclose(autocorr, TTemi_std[0:nsteps], rtol=value[3]))
def FT_DM_hybrid_TDDMRG_TDH(mol, J, nexciton, T, nsteps, pbond, ephtable, \
thresh=0., TDDMRG_prop_method="C_RK4", cleanexciton=None, QNargs=None, space=None):
'''
construct the finite temperature density matrix by hybrid TDDMRG/TDH method
'''
# initial state infinite T density matrix
# TDDMRG
if nexciton == 0:
DMMPS, DMMPSdim = tMPS.Max_Entangled_GS_MPS(mol,
pbond,
norm=True,
QNargs=QNargs)
DMMPO = tMPS.hilbert_to_liouville(DMMPS, QNargs=QNargs)
elif nexciton == 1:
DMMPO, DMMPOdim = tMPS.Max_Entangled_EX_MPO(mol,
pbond,
norm=True,
QNargs=QNargs)
DMMPO = mpslib.MPSdtype_convert(DMMPO, QNargs=QNargs)
# TDH
DMH = []
nmols = len(mol)
for imol in xrange(nmols):
for iph in xrange(mol[imol].nphs_hybrid):
dim = mol[imol].ph_hybrid[iph].H_vib_indep.shape[0]
DMH.append(np.diag([1.0] * dim, k=0))
# the coefficent a
DMH.append(1.0)
mflib.normalize(DMH)
beta = constant.T2beta(T) / 2.0
dbeta = beta / float(nsteps)
for istep in xrange(nsteps):
if space is None:
DMMPO, DMH = hybrid_TDDMRG_TDH(mol, J, DMMPO, DMH, dbeta/1.0j, ephtable, \
thresh=thresh, cleanexciton=cleanexciton, QNargs=QNargs, \
TDDMRG_prop_method=TDDMRG_prop_method, normalize=1.0)
else:
MPOprop, HAM, Etot = ExactPropagator_hybrid_TDDMRG_TDH(mol, J, \
DMMPO, DMH, -1.0*dbeta, space=space, QNargs=QNargs)
DMH[-1] *= np.exp(-1.0 * Etot * dbeta)
TDH.unitary_propagation(HAM, DMH, dbeta / 1.0j)
DMMPO = mpslib.mapply(MPOprop, DMMPO, QNargs=QNargs)
# DMMPO is not normalize in the imaginary time domain
MPOnorm = mpslib.norm(DMMPO, QNargs=QNargs)
DMMPO = mpslib.scale(DMMPO, 1. / MPOnorm, QNargs=QNargs)
DMH[-1] *= MPOnorm
# normlize the dm (physical \otimes ancilla)
mflib.normalize(DMH)
# divided by np.sqrt(partition function)
DMH[-1] = 1.0
return DMMPO, DMH