def test_FT_dynamics_TDH():
log.init_log(logging.WARNING)
mol_list = parameter_PBI.construct_mol(4, dmrg_nphs=0, hartree_nphs=10)
operators = []
for imol in range(len(mol_list)):
dipoleO = tdh.construct_onsiteO(mol_list,
r"a^\dagger a",
dipole=False,
mol_idx_set={imol})
operators.append(dipoleO)
T = Quantity(2000, "K")
insteps = 1
dynamics = tdh.Dynamics(mol_list,
property_ops=operators,
temperature=T,
insteps=insteps)
nsteps = 300 - 1
dt = 10.0
dynamics.evolve(dt, nsteps)
with open(os.path.join(cur_dir, "FT_occ10.npy"), "rb") as f:
std = np.load(f)
assert np.allclose(dynamics.properties, std, atol=1e-2)
def test_FT_dynamics_hybrid_TDDMRG_TDH(n_dmrg_phs, scheme):
mol_list = parameter_PBI.construct_mol(4, n_dmrg_phs, 10 - n_dmrg_phs).switch_scheme(scheme)
mpdm = MpDm.max_entangled_gs(mol_list)
tentative_mpo = Mpo(mol_list)
temperature = Quantity(2000, "K")
tp = ThermalProp(mpdm, tentative_mpo, exact=True, space="GS")
tp.evolve(None, 1, temperature.to_beta() / 2j)
mpdm = (
Mpo.onsite(mol_list, r"a^\dagger", mol_idx_set={0}).apply(tp.latest_mps).normalize(1.0)
)
mpdm.compress_config = CompressConfig(threshold=5e-4)
offset = mpdm.expectation(tentative_mpo)
mpo = Mpo(mol_list, offset=Quantity(offset, "a.u."))
# do the evolution
# nsteps = 90 # too many steps, may take hours to finish
nsteps = 40
dt = 10.0
occ = [mpdm.e_occupations]
for i in range(nsteps):
mpdm = mpdm.evolve(mpo, dt)
occ.append(mpdm.e_occupations)
# make it compatible with std data
occ = np.array(occ[:nsteps]).transpose()
with open(os.path.join(cur_dir, "FT_occ" + str(n_dmrg_phs) + ".npy"), "rb") as f:
std = np.load(f)
assert np.allclose(occ[:, :nsteps], std[:, :nsteps], atol=1e-3, rtol=1e-3)
def test_ZT_dynamics_TDH():
log.init_log(logging.INFO)
sites = 4
mol_list = parameter_PBI.construct_mol(sites, dmrg_nphs=0, hartree_nphs=10)
nsteps = 100 - 1
dt = 10.0
dynamics = tdh.Dynamics(mol_list, init_idx=0)
dynamics.info_interval = 50
dynamics.evolve(dt, nsteps)
with open(os.path.join(cur_dir, "ZT_occ10.npy"), "rb") as f:
std = np.load(f)
assert np.allclose(dynamics.e_occupations_array, std.T, atol=1e-2)
def test_FT_dynamics_TDH():
log.init_log(logging.WARNING)
mol_list = parameter_PBI.construct_mol(4, dmrg_nphs=0, hartree_nphs=10)
T = Quantity(2000, "K")
insteps = 1
dynamics = tdh.Dynamics(mol_list, temperature=T, insteps=insteps)
nsteps = 300 - 1
dt = 10.0
dynamics.evolve(dt, nsteps)
with open(os.path.join(cur_dir, "FT_occ10.npy"), "rb") as f:
std = np.load(f)
assert np.allclose(dynamics.e_occupations_array, std.T, atol=1e-2)
def test_ZT_dynamics_TDH():
log.init_log(logging.INFO)
sites = 4
mol_list = parameter_PBI.construct_mol(sites, dmrg_nphs=0, hartree_nphs=10)
operators = []
nsteps = 100 - 1
dt = 10.0
dynamics = tdh.Dynamics(mol_list, property_ops=operators, init_idx=0)
dynamics.info_interval = 50
dynamics.evolve(dt, nsteps)
electrons = np.array([wfn[0] for wfn in dynamics.tdmps_list])
electrons = (electrons.conj() * electrons).real
# debug code to calculate r
# r_list = []
# for electron in electrons:
# r = np.average(np.arange(sites)**2, weights=electron) - np.average(np.arange(sites), weights=electron) ** 2
# r_list.append(r)
with open(os.path.join(cur_dir, "ZT_occ10.npy"), "rb") as f:
std = np.load(f)
assert np.allclose(electrons.T, std, atol=1e-2)
def test_zt(n_dmrg_phs, scheme):
mol_list = parameter_PBI.construct_mol(4, n_dmrg_phs, 10 - n_dmrg_phs).switch_scheme(scheme)
mps = Mps.gs(mol_list, False)
# create electron
mps = Mpo.onsite(mol_list, r"a^\dagger", mol_idx_set={0}).apply(mps).normalize(1.0)
tentative_mpo = Mpo(mol_list)
offset = mps.expectation(tentative_mpo)
mpo = Mpo(mol_list, offset=Quantity(offset, "a.u."))
# do the evolution
nsteps = 30
dt = 30.0
occ = [mps.e_occupations]
for i in range(nsteps):
mps = mps.evolve(mpo, dt)
occ.append(mps.e_occupations)
# make it compatible with std data
occ = np.array(occ[:nsteps]).transpose()
with open(os.path.join(cur_dir, "ZT_occ" + str(n_dmrg_phs) + ".npy"), "rb") as f:
std = np.load(f)
assert np.allclose(occ, std, rtol=1e-2, atol=1e-4)
gs = Mps.gs(mol_list, max_entangled=False)
assert not gs.ph_occupations.any()
b2 = Mpo.ph_onsite(mol_list, r"b^\dagger", 0, 0)
p1 = b2.apply(gs).normalize()
assert np.allclose(p1.ph_occupations, [1, 0, 0, 0, 0, 0])
p2 = b2.apply(p1).normalize()
assert np.allclose(p2.ph_occupations, [2, 0, 0, 0, 0, 0])
b = b2.conj_trans()
assert b.distance(Mpo.ph_onsite(mol_list, r"b", 0, 0)) == 0
assert b.apply(p2).normalize().distance(p1) == pytest.approx(0, abs=1e-5)
from renormalizer.tests.parameter_PBI import construct_mol
@pytest.mark.parametrize("mol_list", (mol_list, construct_mol(10, 10, 0)))
@pytest.mark.parametrize("scheme", (
123,
4,
))
def test_general_mpo_MolList(mol_list, scheme):
if scheme == 4:
mol_list1 = mol_list.switch_scheme(4)
else:
mol_list1 = mol_list
mol_list1.mol_list2_para()
mpo = Mpo.general_mpo(mol_list1,
const=Quantity(-mol_list1[0].gs_zpe *
mol_list1.mol_num))
def test_symmetry():
assert not mol_list.is_symmetric
assert construct_mol(10, 10, 0).is_symmetric