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_TDH_ZT_abs():
log.init_log(logging.WARNING)
nsteps = 300 - 1
dt = 10.0
E_offset = -2.28614053 / constant.au2ev
ls = tdh.LinearSpectra("abs",
hartree_mol_list,
E_offset=E_offset,
prop_method="unitary")
ls.evolve(dt, nsteps)
with open(os.path.join(cur_dir, "TDH_ZT_abs_prop1.npy"), "rb") as f:
TDH_ZT_abs_prop1_std = np.load(f)
assert np.allclose(ls.autocorr, TDH_ZT_abs_prop1_std)
ls = tdh.LinearSpectra("abs",
hartree_mol_list,
E_offset=E_offset,
prop_method="C_RK4")
ls.evolve(dt, nsteps)
with open(os.path.join(cur_dir, "TDH_ZT_abs_RK4.npy"), "rb") as f:
TDH_ZT_abs_RK4_std = np.load(f)
assert np.allclose(ls.autocorr, TDH_ZT_abs_RK4_std, 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_TDH_ZT_emi():
# disable tons of logging information
log.init_log(logging.WARNING)
nsteps = 3000 - 1
dt = 30.0
ls = tdh.LinearSpectra("emi", hartree_mol_list, prop_method="unitary")
ls.evolve(dt, nsteps)
with open(os.path.join(cur_dir, "TDH_ZT_emi_prop1.npy"), "rb") as f:
TDH_ZT_emi_prop1_std = np.load(f)
assert np.allclose(ls.autocorr, TDH_ZT_emi_prop1_std)
ls = tdh.LinearSpectra("emi", hartree_mol_list, prop_method="C_RK4")
ls.evolve(dt, nsteps)
with open(os.path.join(cur_dir, "TDH_ZT_emi_RK4.npy"), "rb") as f:
TDH_ZT_emi_RK4_std = np.load(f)
assert np.allclose(ls.autocorr, TDH_ZT_emi_RK4_std, rtol=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_1mol_ZTabs():
log.init_log(logging.WARNING)
nmols = 1
mol_list = MolList(
[Mol(elocalex, hartree_ph_list, dipole_abs) for _ in range(nmols)],
np.zeros([1, 1]),
)
E_offset = -mol_list[0].elocalex - mol_list[0].hartree_e0
ls = tdh.LinearSpectra("abs",
mol_list,
E_offset=E_offset,
prop_method="unitary")
nsteps = 1000 - 1
dt = 30.0
ls.evolve(dt, nsteps)
with open(os.path.join(cur_dir, "1mol_ZTabs.npy"), "rb") as f:
mol1_ZTabs_std = np.load(f)
assert np.allclose(ls.autocorr, mol1_ZTabs_std)
# -*- coding: utf-8 -*-
# Author: Jiajun Ren <*****@*****.**>
import os
import sys
if "numpy" in sys.modules:
raise ImportError(
"renormalizer should be imported before numpy is imported")
# set environment variables to limit NumPy cpu usage
# Note that this should be done before NumPy is imported
for env in ["MKL_NUM_THREADS", "NUMEXPR_NUM_THREADS", "OMP_NUM_THREADS"]:
os.environ[env] = "1"
del env
# NEP-18 not working. For compatibility of newer NumPy version. See gh-cupy/cupy#2130
os.environ["NUMPY_EXPERIMENTAL_ARRAY_FUNCTION"] = "0"
del os, sys
from renormalizer.utils.log import init_log
init_log()
del init_log
# -*- coding: utf-8 -*-
import logging
from renormalizer.sbm import SpinBosonDynamics, param2mollist
from renormalizer.utils import Quantity, CompressConfig, EvolveConfig, log
log.init_log(logging.INFO)
if __name__ == "__main__":
alpha = 0.05
raw_delta = Quantity(1)
raw_omega_c = Quantity(20)
n_phonons = 300
renormalization_p = 1
model = param2mollist(alpha, raw_delta, raw_omega_c, renormalization_p,
n_phonons)
compress_config = CompressConfig(threshold=1e-4)
evolve_config = EvolveConfig(adaptive=True, guess_dt=0.1)
sbm = SpinBosonDynamics(model,
Quantity(0),
compress_config=compress_config,
evolve_config=evolve_config,
dump_dir="./",
job_name="sbm")
sbm.evolve(evolve_dt=0.1, evolve_time=20)
