def test_sdf():
alpha = 0.05
omega_c = Quantity(5)
sdf = SpectralDensityFunction(alpha, omega_c)
omega_list, displacement_list = sdf.trapz(200, 0.0, 50)
ph_list = [Phonon.simplest_phonon(o, d) for o,d in zip(omega_list, displacement_list)]
mol_reor = sum(ph.reorganization_energy.as_au() for ph in ph_list)
assert mol_reor == pytest.approx(alpha * omega_c.as_au() / 2, abs=0.005)
def param2mollist(alpha: float, raw_delta: Quantity, omega_c: Quantity,
renormalization_p: float, n_phonons: int):
sdf = SpectralDensityFunction(alpha, omega_c)
delta, max_omega = sdf.adiabatic_renormalization(raw_delta,
renormalization_p)
omega_list, displacement_list = sdf.trapz(n_phonons, 0.0,
max_omega.as_au())
ph_list = [
Phonon.simplest_phonon(o, d)
for o, d in zip(omega_list, displacement_list)
]
return SpinBosonModel(Quantity(0), delta, ph_list)
N_PHONONS = 35
TOTAL_HR = 0.42
if __name__ == "__main__":
omegas_cm = np.linspace(2, 300, N_PHONONS)
omegas_au = omegas_cm * cm2au
hr_factors = np.interp(omegas_cm, sdf_values[:, 0], sdf_values[:, 1])
hr_factors *= TOTAL_HR / hr_factors.sum()
lams = hr_factors * omegas_au
phonons = [
Phonon.simplest_phonon(Quantity(o), Quantity(l), lam=True)
for o, l in zip(omegas_au, lams)
]
j_matrix_au = j_matrix_cm * cm2au
mlist = []
for j in np.diag(j_matrix_au):
m = Mol(Quantity(j), phonons)
mlist.append(m)
# starts from 1
mol_arangement = np.array([7, 5, 3, 1, 2, 4, 6]) - 1
mol_list = MolList(list(np.array(mlist)[mol_arangement]),
j_matrix_au[mol_arangement][:, mol_arangement])
