def test_delta(fname=None):
n_dims = [max_tier] * max_terms
heom = Hierachy(n_dims, H, V, corr)
# Adopt MCTDH
root = simple_heom(rho_0, n_dims)
leaves_dict = {leaf.name: leaf for leaf in root.leaves()}
all_terms = []
for term in heom.diff():
all_terms.append([(leaves_dict[str(fst)], snd) for fst, snd in term])
solver = MultiLayer(root, all_terms)
solver.ode_method = 'RK45'
solver.snd_order = False
solver.atol = 1.e-7
solver.rtol = 1.e-7
# Define the obersevable of interest
logger = Logger(filename=fname, level='info').logger
for n, (time, r) in enumerate(
solver.propagator(
steps=count,
ode_inter=dt_unit,
#split=False,
)):
if n % callback_interval == 0:
rho = np.reshape(r.array, (-1, 4))
logger.info("{} {} {} {} {}".format(time, rho[0, 0], rho[0, 1],
rho[0, 2], rho[0, 3]))
return
def test_heom(fname=None):
n_dims = 2 * dof * [max_tier]
root = simple_heom(rho_0, n_dims)
leaves = root.leaves()
h_list = model.heom_h_list(leaves[0], leaves[1], leaves[2:], beta=None)
solver = MultiLayer(root, h_list)
solver.ode_method = 'RK45'
solver.cmf_steps = solver.max_ode_steps # use constant mean-field
solver.ps_method = 'split'
solver.svd_err = 1.0e-12
# Define the obersevable of interest
logger = Logger(filename=prefix + fname, level='info').logger
logger2 = Logger(filename=prefix + "en_" + fname, level='info').logger
for n, (time, r) in enumerate(
solver.propagator(
steps=count,
ode_inter=dt_unit,
split=False,
)):
# renormalized by the trace of rho
norm = np.trace(np.reshape(np.reshape(r.array, (4, -1))[:, 0], (2, 2)))
r.set_array(r.array / norm)
if n % callback_interval == 0:
t = Quantity(time).convert_to(unit='fs').value
rho = np.reshape(r.array, (4, -1))[:, 0]
logger.info("{} {} {} {} {}".format(t, rho[0], rho[1], rho[2],
rho[3]))
en = np.trace(np.reshape(rho, (2, 2)) @ model.h)
logger2.info('{} {}'.format(t, en))
return
def test_simple(fname=None):
# Type settings
corr.print()
n_dims = [max_tier] * max_terms
heom = Hierachy(n_dims, H, V, corr)
# Adopt MCTDH
root = simple_heom(rho_0, n_dims)
leaves_dict = {leaf.name: leaf for leaf in root.leaves()}
all_terms = []
for term in heom.diff():
all_terms.append([(leaves_dict[str(fst)], snd) for fst, snd in term])
#solver = ProjectorSplitting(root, all_terms)
solver = MultiLayer(root, all_terms)
solver.ode_method = 'RK45'
solver.snd_order = False
# Define the obersevable of interest
logger = Logger(filename=fname, level='info').logger
for n, (time, r) in enumerate(solver.propagator(
steps=count,
ode_inter=dt_unit,
)):
try:
if n % callback_interval == 0:
rho = np.reshape(r.array, (-1, 4))[0]
logger.info("{} {} {} {} {}".format(time, rho[0], rho[1], rho[2], rho[3]))
except:
break
return
def test_simple():
# Type settings
corr = Correlation(k_max=max_terms)
corr.symm_coeff = np.diag(corr_dict['s'].toarray())
corr.asymm_coeff = np.diag(corr_dict['a'].toarray())
corr.exp_coeff = np.diag(corr_dict['gamma'].toarray())
corr.delta_coeff = 0.0 # delta_coeff
corr.print()
n_dims = [max_tier] * max_terms
heom = Hierachy(n_dims, H, V, corr)
# Adopt MCTDH
root = simple_heom(rho_0, n_dims)
leaves_dict = {leaf.name: leaf for leaf in root.leaves()}
all_terms = []
for term in heom.diff():
all_terms.append([(leaves_dict[str(fst)], snd) for fst, snd in term])
#solver = ProjectorSplitting(root, all_terms)
solver = MultiLayer(root, all_terms)
solver.ode_method = 'RK45'
solver.snd_order = False
solver.atol = 1.e-7
solver.rtol = 1.e-7
# Define the obersevable of interest
dat = []
for n, (time,
r) in enumerate(solver.propagator(
steps=count,
ode_inter=dt_unit,
)):
try:
if n % callback_interval == 0:
rho = np.reshape(r.array, (-1, 4))
flat_data = [time] + list(rho[0])
dat.append(flat_data)
print("Time: {}; Tr rho_0: {}".format(
time, rho[0, 0] + rho[0, -1]))
except:
break
return np.array(dat)
def test_drude(fname=None):
# Type settings
corr = Correlation(k_max=max_terms)
corr.symm_coeff = np.diag(corr_dict['s'].toarray())
corr.asymm_coeff = np.diag(corr_dict['a'].toarray())
corr.exp_coeff = np.diag(corr_dict['gamma'].toarray())
corr.delta_coeff = 0.0 # delta_coeff
corr.print()
n_dims = [max_tier] * max_terms
heom = Hierachy(n_dims, H, V, corr)
# Adopt MCTDH
root = simple_heom(rho_0, n_dims)
leaves_dict = {leaf.name: leaf for leaf in root.leaves()}
all_terms = []
for term in heom.diff():
all_terms.append([(leaves_dict[str(fst)], snd) for fst, snd in term])
solver = ProjectorSplitting(root, all_terms)
solver.ode_method = 'DOP853'
solver.snd_order = False
solver.atol = 1.e-7
solver.rtol = 1.e-7
# Define the obersevable of interest
logger = Logger(filename=fname, level='info').logger
for n, (time, r) in enumerate(solver.propagator(
steps=count,
ode_inter=dt_unit,
)):
if n % callback_interval == 0:
rho = np.reshape(r.array, (-1, 4))
logger.info("{} {} {} {} {}".format(time, rho[0, 0], rho[0, 1], rho[0, 2], rho[0, 3]))
print("Time: {}; Tr rho_0: {}".format(time, rho[0, 0] + rho[0, -1]))
return