def setUp(self, verbose=False):
"""Initializes the calculation
"""
self.verbose = verbose
self.time = qr.TimeAxis(0, 1000, 1.0)
self.temperature = 300
pars1 = dict(ftype="OverdampedBrownian",
reorg=30,
cortime=100,
T=self.temperature)
pars2 = dict(ftype="OverdampedBrownian",
reorg=80,
cortime=200,
T=self.temperature)
self.cf1 = qr.CorrelationFunction(self.time, pars1)
self.cf2 = qr.CorrelationFunction(self.time, pars2)
#
# Create aggregate of the two molecules
#
agg = qr.Aggregate(molecules=[m1, m2])
#
# Define time span of the calculation
#
time = qr.TimeAxis(0.0, 10000, 1.0)
#
# Define bath correlation function
#
cpar = dict(ftype="OverdampedBrownian", cortime=30, reorg=200, T=300)
with qr.energy_units("1/cm"):
cf = qr.CorrelationFunction(time, cpar)
#
# Set the correlation function to the transitions on the molecules
#
m1.set_transition_environment((0, 1), cf)
m2.set_transition_environment((0, 1), cf)
#
# Build the aggregate
#
agg.build()
#
# Calculate absorption spectrum
#
t13Count = 300
t2s = qr.TimeAxis(0.0, t2Count, t2Step)
t13 = qr.TimeAxis(0.0, t13Count, t13Step)
timeTotal = qr.TimeAxis(0.0, 3 * t13Count, t13Step)
two_pi = np.pi * 2
proteinDis = 8.7
difference = 0.6
temperature = 300
params = dict(ftype="OverdampedBrownian",
T=temperature,
reorg=reorganisation,
cortime=100.0)
with qr.energy_units('1/cm'):
cf = qr.CorrelationFunction(timeTotal, params)
#cf = CorrelationFunction(ta, params)
#######################################################################
# Creation of the aggregate basic
#######################################################################
while difference > 0.1:
t = np.linspace(0, two_pi, numMol + 1)
x = r * np.cos(t)
y = r * np.sin(t)
circle = np.c_[x, y]
artificialDis = math.sqrt(((circle[0][0] - circle[1][0])**2) +
((circle[0][1] - circle[1][1])**2))
difference = abs(artificialDis - proteinDis)
"""
cfce_params1 = dict(ftype="OverdampedBrownian",
reorg=20.0,
cortime=100.0,
T=100,
matsubara=20)
en = 12000.0
e_units = qr.energy_units("1/cm")
with e_units:
m = qr.Molecule("Molecule", [0.0, en])
with qr.energy_units("1/cm"):
cfce1 = qr.CorrelationFunction(ta, cfce_params1)
m.set_egcf((0, 1), cfce1)
m.set_dipole(0, 1, [0.0, 1.0, 0.0])
a1 = qr.AbsSpect(ta, m)
with qr.energy_units("1/cm"):
a1.calculate(rwa=en)
HH = m.get_Hamiltonian()
with qr.frequency_units("1/cm"):
print(HH)
a1.plot(axis=[11500, 12500, 0, numpy.max(a1.data) * 1.1])
save_load = False
m2 = qr.Molecule([0.0, 12300.0])
# correlation functions the environment
#
cfce_params1 = dict(ftype="OverdampedBrownian",
reorg=40.0,
cortime=100.0,
T=100,
matsubara=20)
cfce_params2 = dict(ftype="OverdampedBrownian",
reorg=40.0,
cortime=100.0,
T=100,
matsubara=20)
cfce1 = qr.CorrelationFunction(t_axis, cfce_params1)
cfce2 = qr.CorrelationFunction(t_axis, cfce_params2)
m1.set_transition_environment((0, 1), cfce1)
m2.set_transition_environment((0, 1), cfce2)
# we create an aggregate from the two molecules
agg = qr.Aggregate(molecules=[m1, m2])
# we set transition dipole moment orientations for the two molecules
m1.set_dipole(0, 1, [1.0, 0.8, 0.8])
m2.set_dipole(0, 1, [0.8, 0.8, 0.0])
# resonance coupling is set by hand
with qr.energy_units("1/cm"):
agg.set_resonance_coupling(0, 1, 100.0)
for i_m in range(N_molecules):
mod = qr.Mode(vomega)
mols[i_m].add_Mode(mod)
mod.set_nmax(0, Ng_max)
mod.set_nmax(1, Ne_max)
mod.set_HR(1, hr_fac)
# Bath correlation functions
timea = qr.TimeAxis(0.0, 1000, 1.0)
cfpar = dict(ftype="OverdampedBrownian",
reorg=30,
cortime=100,
T=300,
matsubara=100)
with qr.energy_units("1/cm"):
cf = qr.CorrelationFunction(timea, cfpar)
# set bath correlation functions to the molecules
for i_m in range(N_molecules):
mols[i_m].set_transition_environment((0, 1), cf)
# aggregate of molecules
agg = qr.Aggregate(mols)
agg.set_coupling_by_dipole_dipole()
# Building the aggregate
qr.log_report("Building aggregate")
agg.build()
qr.log_report("...done")
#
# Setting up laboratory
#
lab = lab_settings(lab_settings.FOUR_WAVE_MIXING)
a_0 = numpy.array([1.0, 0.0, 0.0], dtype=numpy.float64)
lab.set_laser_polarizations(a_0,a_0,a_0,a_0)
#
# System-bath interaction
#
tsbi = qr.TimeAxis(0.0, 3*Nr, 1.0)
params = dict(ftype="OverdampedBrownian", T=300, reorg=100.0, cortime=50.0)
with qr.energy_units('1/cm'):
cf = qr.CorrelationFunction(tsbi, params)
params2 = dict(ftype="UnderdampedBrownian", T=300, reorg=10.0, freq=150.0,
gamma=1.0/10000.0)
with qr.energy_units('1/cm'):
cf2 = qr.CorrelationFunction(tsbi, params2)
#cf.add_to_data(cf2)
##
## Set system-bath interaction
##
#mol1.set_transition_environment((0,1),cf)
#mol2.set_transition_environment((0,1),cf)
#mol3.set_transition_environment((0,1),cf)
agg.set_resonance_coupling(0, 1, 80.0)
agg.set_resonance_coupling(0, 2, 100.0)
# Interaction with the bath is set through bath correlation functions
timea = qr.TimeAxis(0.0, 500, 1.0)
cpar1 = dict(ftype="OverdampedBrownian-HighTemperature",
reorg=50,
cortime=50,
T=300)
cpar2 = dict(ftype="OverdampedBrownian-HighTemperature",
reorg=50,
cortime=50,
T=300)
with qr.energy_units("1/cm"):
cfce1 = qr.CorrelationFunction(timea, cpar1)
cfce2 = qr.CorrelationFunction(timea, cpar2)
m1.set_transition_environment((0, 1), cfce1)
m2.set_transition_environment((0, 1), cfce1)
m3.set_transition_environment((0, 1), cfce2)
# Aggregate is built
agg.build()
###############################################################################
#
# Definition of the hierarchy
#
###############################################################################
m.set_energy(1, 12320.0)
m = agg.get_Molecule_by_name("BChl6")
m.set_energy(1, 12593.0)
m = agg.get_Molecule_by_name("BChl7")
m.set_energy(1, 12353.0)
#
# Set resonance coupling by dipole-dipole method
#
agg.set_coupling_by_dipole_dipole(epsr=1.21)
# Setting spectral density to all molecules
tmax = qr.TimeAxis(0.0, 1000, 1.0)
param = dict(ftype="OverdampedBrownian", reorg=50, cortime=50, T=300)
with qr.energy_units("1/cm"):
cfce = qr.CorrelationFunction(tmax, param)
for mol in agg.monomers:
mol.set_transition_environment((0, 1), cfce)
#
# Build the aggregate
#
agg.build()
#
# Now we can start simulations
#
H = agg.get_Hamiltonian()
with energy_units("1/cm"):
cortime=100,
T=77,
matsubara=100)
cfP_params = dict(ftype="OverdampedBrownian",
reorg=700,
cortime=120,
T=77,
matsubara=100)
cfCT_params = dict(ftype="OverdampedBrownian",
reorg=3600,
cortime=20,
T=77,
matsubara=200)
with qr.energy_units("1/cm"):
cfA = qr.CorrelationFunction(time, cfA_params)
cfH = qr.CorrelationFunction(time, cfH_params)
cfP = qr.CorrelationFunction(time, cfP_params)
cfCT = qr.CorrelationFunction(time, cfCT_params)
PM.set_transition_environment((0, 1), cfP)
PL.set_transition_environment((0, 1), cfP)
BM.set_transition_environment((0, 1), cfA)
BL.set_transition_environment((0, 1), cfA)
HL.set_transition_environment((0, 1), cfH)
HM.set_transition_environment((0, 1), cfH)
PCT_M.set_transition_environment((0, 1), cfCT)
PCT_L.set_transition_environment((0, 1), cfCT)
agg.build(mult=2)
#agg.save("RC_Model_40_4_adjusted_CT_no_vibrations_built.hdf5")
