def calculate_energy(self, pd, chi0_wGG, cut_G, q_v=None):
"""Evaluate correlation energy from chi0."""
sqrV_G = get_coulomb_kernel(pd,
self.calc.wfs.kd.N_c,
q_v=q_v,
truncation=self.truncation,
wstc=self.wstc)**0.5
if cut_G is not None:
sqrV_G = sqrV_G[cut_G]
nG = len(sqrV_G)
e_w = []
for chi0_GG in chi0_wGG:
if cut_G is not None:
chi0_GG = chi0_GG.take(cut_G, 0).take(cut_G, 1)
e_GG = np.eye(nG) - chi0_GG * sqrV_G * sqrV_G[:, np.newaxis]
e = np.log(np.linalg.det(e_GG)) + nG - np.trace(e_GG)
e_w.append(e.real)
E_w = np.zeros_like(self.omega_w)
self.blockcomm.all_gather(np.array(e_w), E_w)
energy = np.dot(E_w, self.weight_w) / (2 * np.pi)
self.E_w = E_w
return energy
def get_dielectric_matrix(self,
xc='RPA',
q_c=[0, 0, 0],
direction='x',
symmetric=True,
calculate_chi=False,
q_v=None,
add_intraband=True):
"""Returns the symmetrized dielectric matrix.
::
\tilde\epsilon_GG' = v^{-1/2}_G \epsilon_GG' v^{1/2}_G',
where::
epsilon_GG' = 1 - v_G * P_GG' and P_GG'
is the polarization.
::
In RPA: P = chi^0
In TDDFT: P = (1 - chi^0 * f_xc)^{-1} chi^0
in addition to RPA one can use the kernels, ALDA, rALDA, rAPBE,
Bootstrap and LRalpha (long-range kerne), where alpha is a user
specified parameter (for example xc='LR0.25')
The head of the inverse symmetrized dielectric matrix is equal
to the head of the inverse dielectric matrix (inverse dielectric
function)"""
pd, chi0_wGG, chi0_wxvG, chi0_wvv = self.calculate_chi0(q_c)
N_c = self.chi0.calc.wfs.kd.N_c
if self.truncation == 'wigner-seitz':
self.wstc = WignerSeitzTruncatedCoulomb(pd.gd.cell_cv, N_c)
else:
self.wstc = None
K_G = get_coulomb_kernel(pd,
N_c,
truncation=self.truncation,
wstc=self.wstc,
q_v=q_v)**0.5
nG = len(K_G)
if pd.kd.gamma:
if isinstance(direction, str):
d_v = {
'x': [1, 0, 0],
'y': [0, 1, 0],
'z': [0, 0, 1]
}[direction]
else:
d_v = direction
d_v = np.asarray(d_v) / np.linalg.norm(d_v)
W = slice(self.w1, self.w2)
if add_intraband:
chi0_wGG[:, 0] = np.dot(d_v, chi0_wxvG[W, 0])
chi0_wGG[:, :, 0] = np.dot(d_v, chi0_wxvG[W, 1])
chi0_wGG[:, 0, 0] = np.dot(d_v, np.dot(chi0_wvv[W], d_v).T)
if q_v is not None:
print('Restoring q dependence of head and wings of chi0')
chi0_wGG[:, 1:, 0] *= np.dot(q_v, d_v)
chi0_wGG[:, 0, 1:] *= np.dot(q_v, d_v)
chi0_wGG[:, 0, 0] *= np.dot(q_v, d_v)**2
if xc != 'RPA':
Kxc_sGG = get_xc_kernel(pd,
self.chi0,
functional=xc,
chi0_wGG=chi0_wGG)
if calculate_chi:
chi_wGG = []
for chi0_GG in chi0_wGG:
if xc == 'RPA':
P_GG = chi0_GG
else:
P_GG = np.dot(
np.linalg.inv(np.eye(nG) - np.dot(chi0_GG, Kxc_sGG[0])),
chi0_GG)
if symmetric:
e_GG = np.eye(nG) - P_GG * K_G * K_G[:, np.newaxis]
else:
K_GG = (K_G**2 * np.ones([nG, nG])).T
e_GG = np.eye(nG) - P_GG * K_GG
if calculate_chi:
K_GG = np.diag(K_G**2)
if xc != 'RPA':
K_GG += Kxc_sGG[0]
chi_wGG.append(
np.dot(np.linalg.inv(np.eye(nG) - np.dot(chi0_GG, K_GG)),
chi0_GG))
chi0_GG[:] = e_GG
# chi0_wGG is now the dielectric matrix
if not calculate_chi:
return chi0_wGG
else:
# chi_wGG is the full density response function..
return pd, chi0_wGG, np.array(chi_wGG)
def get_chi(self,
xc='RPA',
q_c=[0, 0, 0],
direction='x',
return_VchiV=True,
q_v=None):
""" Returns v^1/2 chi v^1/2. The truncated Coulomb interaction is
then included as v^-1/2 v_t v^-1/2. This is in order to conform with
the head and wings of chi0, which is treated specially for q=0."""
pd, chi0_wGG, chi0_wxvG, chi0_wvv = self.calculate_chi0(q_c)
N_c = self.chi0.calc.wfs.kd.N_c
Kbare_G = get_coulomb_kernel(pd, N_c, truncation=None, q_v=q_v)
vsqr_G = Kbare_G**0.5
nG = len(vsqr_G)
if self.truncation is not None:
if self.truncation == 'wigner-seitz':
self.wstc = WignerSeitzTruncatedCoulomb(pd.gd.cell_cv, N_c)
else:
self.wstc = None
Ktrunc_G = get_coulomb_kernel(pd,
N_c,
truncation=self.truncation,
wstc=self.wstc,
q_v=q_v)
K_GG = np.diag(Ktrunc_G / Kbare_G)
else:
K_GG = np.eye(nG, dtype=complex)
if pd.kd.gamma:
if isinstance(direction, str):
d_v = {
'x': [1, 0, 0],
'y': [0, 1, 0],
'z': [0, 0, 1]
}[direction]
else:
d_v = direction
d_v = np.asarray(d_v) / np.linalg.norm(d_v)
W = slice(self.w1, self.w2)
chi0_wGG[:, 0] = np.dot(d_v, chi0_wxvG[W, 0])
chi0_wGG[:, :, 0] = np.dot(d_v, chi0_wxvG[W, 1])
chi0_wGG[:, 0, 0] = np.dot(d_v, np.dot(chi0_wvv[W], d_v).T)
if xc != 'RPA':
Kxc_sGG = get_xc_kernel(pd,
self.chi0,
functional=xc,
chi0_wGG=chi0_wGG)
K_GG += Kxc_sGG[0] / vsqr_G / vsqr_G[:, np.newaxis]
chi_wGG = []
for chi0_GG in chi0_wGG:
"""v^1/2 chi0 V^1/2"""
chi0_GG[:] = chi0_GG * vsqr_G * vsqr_G[:, np.newaxis]
chi_GG = np.dot(np.linalg.inv(np.eye(nG) - np.dot(chi0_GG, K_GG)),
chi0_GG)
if not return_VchiV:
chi0_GG /= vsqr_G * vsqr_G[:, np.newaxis]
chi_GG /= vsqr_G * vsqr_G[:, np.newaxis]
chi_wGG.append(chi_GG)
return pd, chi0_wGG, np.array(chi_wGG)
def calculate_screened_potential(self, ac):
"""Calculate W_GG(q)"""
chi0 = Chi0(self.calc,
frequencies=[0.0],
eta=0.001,
ecut=self.ecut,
intraband=False,
hilbert=False,
nbands=self.nbands,
txt='chi0.txt',
world=world,
)
self.blockcomm = chi0.blockcomm
wfs = self.calc.wfs
self.Q_qaGii = []
self.W_qGG = []
self.pd_q = []
t0 = time()
print('Calculating screened potential', file=self.fd)
for iq, q_c in enumerate(self.qd.ibzk_kc):
thisqd = KPointDescriptor([q_c])
pd = PWDescriptor(self.ecut, wfs.gd, complex, thisqd)
nG = pd.ngmax
chi0.Ga = self.blockcomm.rank * nG
chi0.Gb = min(chi0.Ga + nG, nG)
chi0_wGG = np.zeros((1, nG, nG), complex)
if np.allclose(q_c, 0.0):
chi0_wxvG = np.zeros((1, 2, 3, nG), complex)
chi0_wvv = np.zeros((1, 3, 3), complex)
else:
chi0_wxvG = None
chi0_wvv = None
chi0._calculate(pd, chi0_wGG, chi0_wxvG, chi0_wvv,
0, self.nbands, spins='all', extend_head=False)
chi0_GG = chi0_wGG[0]
# Calculate eps^{-1}_GG
if pd.kd.gamma:
# Generate fine grid in vicinity of gamma
kd = self.calc.wfs.kd
N = 4
N_c = np.array([N, N, N])
if self.truncation is not None:
# Only average periodic directions if trunction is used
N_c[kd.N_c == 1] = 1
qf_qc = monkhorst_pack(N_c) / kd.N_c
qf_qc *= 1.0e-6
U_scc = kd.symmetry.op_scc
qf_qc = kd.get_ibz_q_points(qf_qc, U_scc)[0]
weight_q = kd.q_weights
qf_qv = 2 * np.pi * np.dot(qf_qc, pd.gd.icell_cv)
a_q = np.sum(np.dot(chi0_wvv[0], qf_qv.T) * qf_qv.T, axis=0)
a0_qG = np.dot(qf_qv, chi0_wxvG[0, 0])
a1_qG = np.dot(qf_qv, chi0_wxvG[0, 1])
einv_GG = np.zeros((nG, nG), complex)
# W_GG = np.zeros((nG, nG), complex)
for iqf in range(len(qf_qv)):
chi0_GG[0] = a0_qG[iqf]
chi0_GG[:, 0] = a1_qG[iqf]
chi0_GG[0, 0] = a_q[iqf]
sqrV_G = get_coulomb_kernel(pd,
kd.N_c,
truncation=self.truncation,
wstc=self.wstc,
q_v=qf_qv[iqf])**0.5
sqrV_G *= ac**0.5 # Multiply by adiabatic coupling
e_GG = np.eye(nG) - chi0_GG * sqrV_G * sqrV_G[:,
np.newaxis]
einv_GG += np.linalg.inv(e_GG) * weight_q[iqf]
# einv_GG = np.linalg.inv(e_GG) * weight_q[iqf]
# W_GG += (einv_GG * sqrV_G * sqrV_G[:, np.newaxis]
# * weight_q[iqf])
else:
sqrV_G = get_coulomb_kernel(pd,
self.kd.N_c,
truncation=self.truncation,
wstc=self.wstc)**0.5
sqrV_G *= ac**0.5 # Multiply by adiabatic coupling
e_GG = np.eye(nG) - chi0_GG * sqrV_G * sqrV_G[:, np.newaxis]
einv_GG = np.linalg.inv(e_GG)
# W_GG = einv_GG * sqrV_G * sqrV_G[:, np.newaxis]
# Now calculate W_GG
if pd.kd.gamma:
# Reset bare Coulomb interaction
sqrV_G = get_coulomb_kernel(pd,
self.kd.N_c,
truncation=self.truncation,
wstc=self.wstc)**0.5
W_GG = einv_GG * sqrV_G * sqrV_G[:, np.newaxis]
if self.integrate_gamma != 0:
# Numerical integration of Coulomb interaction at all q-points
if self.integrate_gamma == 2:
reduced = True
else:
reduced = False
V0, sqrV0 = get_integrated_kernel(pd,
self.kd.N_c,
truncation=self.truncation,
reduced=reduced,
N=100)
W_GG[0, 0] = einv_GG[0, 0] * V0
W_GG[0, 1:] = einv_GG[0, 1:] * sqrV0 * sqrV_G[1:]
W_GG[1:, 0] = einv_GG[1:, 0] * sqrV_G[1:] * sqrV0
elif self.integrate_gamma == 0 and pd.kd.gamma:
# Analytical integration at gamma
bzvol = (2 * np.pi)**3 / self.vol / self.qd.nbzkpts
Rq0 = (3 * bzvol / (4 * np.pi))**(1. / 3.)
V0 = 16 * np.pi**2 * Rq0 / bzvol
sqrV0 = (4 * np.pi)**(1.5) * Rq0**2 / bzvol / 2
W_GG[0, 0] = einv_GG[0, 0] * V0
W_GG[0, 1:] = einv_GG[0, 1:] * sqrV0 * sqrV_G[1:]
W_GG[1:, 0] = einv_GG[1:, 0] * sqrV_G[1:] * sqrV0
else:
pass
if pd.kd.gamma:
e = 1 / einv_GG[0, 0].real
print(' RPA dielectric constant is: %3.3f' % e,
file=self.fd)
self.Q_qaGii.append(chi0.Q_aGii)
self.pd_q.append(pd)
self.W_qGG.append(W_GG)
if iq % (self.qd.nibzkpts // 5 + 1) == 2:
dt = time() - t0
tleft = dt * self.qd.nibzkpts / (iq + 1) - dt
print(' Finished %s q-points in %s - Estimated %s left' %
(iq + 1, timedelta(seconds=round(dt)),
timedelta(seconds=round(tleft))), file=self.fd)
def calculate(self, optical=True, ac=1.0):
if self.spinors:
"""Calculate spinors. Here m is index of eigenvalues with SOC
and n is the basis of eigenstates withour SOC. Below m is used
for unoccupied states and n is used for occupied states so be
careful!"""
print('Diagonalizing spin-orbit Hamiltonian', file=self.fd)
param = self.calc.parameters
if not param['symmetry'] == 'off':
print('Calculating KS wavefunctions without symmetry ' +
'for spin-orbit', file=self.fd)
if not op.isfile('gs_nosym.gpw'):
calc_so = GPAW(**param)
calc_so.set(symmetry='off',
fixdensity=True,
txt='gs_nosym.txt')
calc_so.atoms = self.calc.atoms
calc_so.density = self.calc.density
calc_so.get_potential_energy()
calc_so.write('gs_nosym.gpw')
calc_so = GPAW('gs_nosym.gpw', txt=None,
communicator=serial_comm)
e_mk, v_knm = get_spinorbit_eigenvalues(calc_so,
return_wfs=True,
scale=self.scale)
del calc_so
else:
e_mk, v_knm = get_spinorbit_eigenvalues(self.calc,
return_wfs=True,
scale=self.scale)
e_mk /= Hartree
# Parallelization stuff
nK = self.kd.nbzkpts
myKrange, myKsize, mySsize = self.parallelisation_sizes()
# Calculate exchange interaction
qd0 = KPointDescriptor([self.q_c])
pd0 = PWDescriptor(self.ecut, self.calc.wfs.gd, complex, qd0)
ikq_k = self.kd.find_k_plus_q(self.q_c)
v_G = get_coulomb_kernel(pd0, self.kd.N_c, truncation=self.truncation,
wstc=self.wstc)
if optical:
v_G[0] = 0.0
self.pair = PairDensity(self.calc, self.ecut, world=serial_comm,
txt='pair.txt')
# Calculate direct (screened) interaction and PAW corrections
if self.mode == 'RPA':
Q_aGii = self.pair.initialize_paw_corrections(pd0)
else:
self.get_screened_potential(ac=ac)
if (self.qd.ibzk_kc - self.q_c < 1.0e-6).all():
iq0 = self.qd.bz2ibz_k[self.kd.where_is_q(self.q_c,
self.qd.bzk_kc)]
Q_aGii = self.Q_qaGii[iq0]
else:
Q_aGii = self.pair.initialize_paw_corrections(pd0)
# Calculate pair densities, eigenvalues and occupations
so = self.spinors + 1
Nv, Nc = so * self.nv, so * self.nc
Ns = self.spins
rhoex_KsmnG = np.zeros((nK, Ns, Nv, Nc, len(v_G)), complex)
# rhoG0_Ksmn = np.zeros((nK, Ns, Nv, Nc), complex)
df_Ksmn = np.zeros((nK, Ns, Nv, Nc), float) # -(ev - ec)
deps_ksmn = np.zeros((myKsize, Ns, Nv, Nc), float) # -(fv - fc)
if np.allclose(self.q_c, 0.0):
optical_limit = True
else:
optical_limit = False
get_pair = self.pair.get_kpoint_pair
get_rho = self.pair.get_pair_density
if self.spinors:
# Get all pair densities to allow for SOC mixing
# Use twice as many no-SOC states as BSE bands to allow mixing
vi_s = [2 * self.val_sn[0, 0] - self.val_sn[0, -1] - 1]
vf_s = [2 * self.con_sn[0, -1] - self.con_sn[0, 0] + 2]
if vi_s[0] < 0:
vi_s[0] = 0
ci_s, cf_s = vi_s, vf_s
ni, nf = vi_s[0], vf_s[0]
mvi = 2 * self.val_sn[0, 0]
mvf = 2 * (self.val_sn[0, -1] + 1)
mci = 2 * self.con_sn[0, 0]
mcf = 2 * (self.con_sn[0, -1] + 1)
else:
vi_s, vf_s = self.val_sn[:, 0], self.val_sn[:, -1] + 1
ci_s, cf_s = self.con_sn[:, 0], self.con_sn[:, -1] + 1
for ik, iK in enumerate(myKrange):
for s in range(Ns):
pair = get_pair(pd0, s, iK,
vi_s[s], vf_s[s], ci_s[s], cf_s[s])
m_m = np.arange(vi_s[s], vf_s[s])
n_n = np.arange(ci_s[s], cf_s[s])
if self.gw_skn is not None:
iKq = self.calc.wfs.kd.find_k_plus_q(self.q_c, [iK])[0]
epsv_m = self.gw_skn[s, iK, :self.nv]
epsc_n = self.gw_skn[s, iKq, self.nv:]
deps_ksmn[ik] = -(epsv_m[:, np.newaxis] - epsc_n)
elif self.spinors:
iKq = self.calc.wfs.kd.find_k_plus_q(self.q_c, [iK])[0]
epsv_m = e_mk[mvi:mvf, iK]
epsc_n = e_mk[mci:mcf, iKq]
deps_ksmn[ik, s] = -(epsv_m[:, np.newaxis] - epsc_n)
else:
deps_ksmn[ik, s] = -pair.get_transition_energies(m_m, n_n)
df_mn = pair.get_occupation_differences(self.val_sn[s],
self.con_sn[s])
rho_mnG = get_rho(pd0, pair,
m_m, n_n,
optical_limit=optical_limit,
direction=self.direction,
Q_aGii=Q_aGii,
extend_head=False)
if self.spinors:
if optical_limit:
deps0_mn = -pair.get_transition_energies(m_m, n_n)
rho_mnG[:, :, 0] *= deps0_mn
df_Ksmn[iK, s, ::2, ::2] = df_mn
df_Ksmn[iK, s, ::2, 1::2] = df_mn
df_Ksmn[iK, s, 1::2, ::2] = df_mn
df_Ksmn[iK, s, 1::2, 1::2] = df_mn
vecv0_nm = v_knm[iK][::2][ni:nf, mvi:mvf]
vecc0_nm = v_knm[iKq][::2][ni:nf, mci:mcf]
rho_0mnG = np.dot(vecv0_nm.T.conj(),
np.dot(vecc0_nm.T, rho_mnG))
vecv1_nm = v_knm[iK][1::2][ni:nf, mvi:mvf]
vecc1_nm = v_knm[iKq][1::2][ni:nf, mci:mcf]
rho_1mnG = np.dot(vecv1_nm.T.conj(),
np.dot(vecc1_nm.T, rho_mnG))
rhoex_KsmnG[iK, s] = rho_0mnG + rho_1mnG
if optical_limit:
rhoex_KsmnG[iK, s, :, :, 0] /= deps_ksmn[ik, s]
else:
df_Ksmn[iK, s] = pair.get_occupation_differences(m_m, n_n)
rhoex_KsmnG[iK, s] = rho_mnG
if self.eshift is not None:
deps_ksmn[np.where(df_Ksmn[myKrange] > 1.0e-3)] += self.eshift
deps_ksmn[np.where(df_Ksmn[myKrange] < -1.0e-3)] -= self.eshift
world.sum(df_Ksmn)
world.sum(rhoex_KsmnG)
self.rhoG0_S = np.reshape(rhoex_KsmnG[:, :, :, :, 0], -1)
if hasattr(self, 'H_sS'):
return
# Calculate Hamiltonian
t0 = time()
print('Calculating %s matrix elements at q_c = %s'
% (self.mode, self.q_c), file=self.fd)
H_ksmnKsmn = np.zeros((myKsize, Ns, Nv, Nc, nK, Ns, Nv, Nc), complex)
for ik1, iK1 in enumerate(myKrange):
for s1 in range(Ns):
kptv1 = self.pair.get_k_point(s1, iK1, vi_s[s1], vf_s[s1])
kptc1 = self.pair.get_k_point(s1, ikq_k[iK1], ci_s[s1],
cf_s[s1])
rho1_mnG = rhoex_KsmnG[iK1, s1]
#rhoG0_Ksmn[iK1, s1] = rho1_mnG[:, :, 0]
rho1ccV_mnG = rho1_mnG.conj()[:, :] * v_G
for s2 in range(Ns):
for Q_c in self.qd.bzk_kc:
iK2 = self.kd.find_k_plus_q(Q_c, [kptv1.K])[0]
rho2_mnG = rhoex_KsmnG[iK2, s2]
rho2_mGn = np.swapaxes(rho2_mnG, 1, 2)
H_ksmnKsmn[ik1, s1, :, :, iK2, s2, :, :] += (
np.dot(rho1ccV_mnG, rho2_mGn))
if not self.mode == 'RPA' and s1 == s2:
ikq = ikq_k[iK2]
kptv2 = self.pair.get_k_point(s1, iK2, vi_s[s1],
vf_s[s1])
kptc2 = self.pair.get_k_point(s1, ikq, ci_s[s1],
cf_s[s1])
rho3_mmG, iq = self.get_density_matrix(kptv1,
kptv2)
rho4_nnG, iq = self.get_density_matrix(kptc1,
kptc2)
if self.spinors:
vec0_nm = v_knm[iK1][::2][ni:nf, mvi:mvf]
vec1_nm = v_knm[iK1][1::2][ni:nf, mvi:mvf]
vec2_nm = v_knm[iK2][::2][ni:nf, mvi:mvf]
vec3_nm = v_knm[iK2][1::2][ni:nf, mvi:mvf]
rho_0mnG = np.dot(vec0_nm.T.conj(),
np.dot(vec2_nm.T, rho3_mmG))
rho_1mnG = np.dot(vec1_nm.T.conj(),
np.dot(vec3_nm.T, rho3_mmG))
rho3_mmG = rho_0mnG + rho_1mnG
vec0_nm = v_knm[ikq_k[iK1]][::2][ni:nf, mci:mcf]
vec1_nm = v_knm[ikq_k[iK1]][1::2][ni:nf,mci:mcf]
vec2_nm = v_knm[ikq][::2][ni:nf, mci:mcf]
vec3_nm = v_knm[ikq][1::2][ni:nf, mci:mcf]
rho_0mnG = np.dot(vec0_nm.T.conj(),
np.dot(vec2_nm.T, rho4_nnG))
rho_1mnG = np.dot(vec1_nm.T.conj(),
np.dot(vec3_nm.T, rho4_nnG))
rho4_nnG = rho_0mnG + rho_1mnG
rho3ccW_mmG = np.dot(rho3_mmG.conj(),
self.W_qGG[iq])
W_mmnn = np.dot(rho3ccW_mmG,
np.swapaxes(rho4_nnG, 1, 2))
W_mnmn = np.swapaxes(W_mmnn, 1, 2) * Ns * so
H_ksmnKsmn[ik1, s1, :, :, iK2, s1] -= 0.5 * W_mnmn
if iK1 % (myKsize // 5 + 1) == 0:
dt = time() - t0
tleft = dt * myKsize / (iK1 + 1) - dt
print(' Finished %s pair orbitals in %s - Estimated %s left' %
((iK1 + 1) * Nv * Nc * Ns * world.size,
timedelta(seconds=round(dt)),
timedelta(seconds=round(tleft))), file=self.fd)
#if self.mode == 'BSE':
# del self.Q_qaGii, self.W_qGG, self.pd_q
H_ksmnKsmn /= self.vol
mySsize = myKsize * Nv * Nc * Ns
if myKsize > 0:
iS0 = myKrange[0] * Nv * Nc * Ns
#world.sum(rhoG0_Ksmn)
#self.rhoG0_S = np.reshape(rhoG0_Ksmn, -1)
self.df_S = np.reshape(df_Ksmn, -1)
if not self.td:
self.excludef_S = np.where(np.abs(self.df_S) < 0.001)[0]
# multiply by 2 when spin-paired and no SOC
self.df_S *= 2.0 / nK / Ns / so
self.deps_s = np.reshape(deps_ksmn, -1)
H_sS = np.reshape(H_ksmnKsmn, (mySsize, self.nS))
for iS in range(mySsize):
# Multiply by occupations and adiabatic coupling
H_sS[iS] *= self.df_S[iS0 + iS] * ac
# add bare transition energies
H_sS[iS, iS0 + iS] += self.deps_s[iS]
self.H_sS = H_sS
if self.write_h:
self.par_save('H_SS.ulm', 'H_SS', self.H_sS)
def get_chi(self,
xc='RPA',
q_c=[0, 0, 0],
spin='all',
direction='x',
return_VchiV=True,
q_v=None,
RSrep='gpaw',
spinpol_cut=None,
density_cut=None,
fxc_scaling=None):
""" Returns v^1/2 chi v^1/2 for the density response and chi for the
spin response. The truncated Coulomb interaction is included as
v^-1/2 v_t v^-1/2. This is in order to conform with
the head and wings of chi0, which is treated specially for q=0.
spin : str or int
If 'all' then include all spins.
If 0 or 1, only include this specific spin.
(not used in transverse reponse functions)
RSrep : str
real space representation of kernel ('gpaw' or 'grid')
spinpol_cut : float
cutoff spin polarization below which f_xc is evaluated in
unpolarized limit (make sure divergent terms cancel out correctly)
density_cut : float
cutoff density below which f_xc is set to zero
fxc_scaling : list
Possible scaling of kernel to hit Goldstone mode.
If w=0 is included in the present calculation and
fxc_scaling=[True, None], the fxc_scaling to match
kappaM_w[0] = 0. will be calculated. If
fxc_scaling = [True, float], Kxc will be scaled by float.
Default is None, i.e. no scaling
"""
# XXX generalize to kernel check
response = self.chi0.response
if response in ['+-', '-+']:
assert xc in ('ALDA_x', 'ALDA_X', 'ALDA')
pd, chi0_wGG, chi0_wxvG, chi0_wvv = self.calculate_chi0(q_c, spin)
if response == 'density':
N_c = self.chi0.calc.wfs.kd.N_c
Kbare_G = get_coulomb_kernel(pd, N_c, truncation=None, q_v=q_v)
vsqr_G = Kbare_G**0.5
nG = len(vsqr_G)
if self.truncation is not None:
if self.truncation == 'wigner-seitz':
self.wstc = WignerSeitzTruncatedCoulomb(pd.gd.cell_cv, N_c)
else:
self.wstc = None
Ktrunc_G = get_coulomb_kernel(pd,
N_c,
truncation=self.truncation,
wstc=self.wstc,
q_v=q_v)
K_GG = np.diag(Ktrunc_G / Kbare_G)
else:
K_GG = np.eye(nG, dtype=complex)
if pd.kd.gamma:
if isinstance(direction, str):
d_v = {
'x': [1, 0, 0],
'y': [0, 1, 0],
'z': [0, 0, 1]
}[direction]
else:
d_v = direction
d_v = np.asarray(d_v) / np.linalg.norm(d_v)
W = slice(self.w1, self.w2)
chi0_wGG[:, 0] = np.dot(d_v, chi0_wxvG[W, 0])
chi0_wGG[:, :, 0] = np.dot(d_v, chi0_wxvG[W, 1])
chi0_wGG[:, 0, 0] = np.dot(d_v, np.dot(chi0_wvv[W], d_v).T)
if xc != 'RPA':
Kxc_GG = get_xc_kernel(pd,
self.chi0,
functional=xc,
chi0_wGG=chi0_wGG,
density_cut=density_cut)
K_GG += Kxc_GG / vsqr_G / vsqr_G[:, np.newaxis]
# Invert Dyson eq.
chi_wGG = []
for chi0_GG in chi0_wGG:
"""v^1/2 chi0 V^1/2"""
chi0_GG[:] = chi0_GG * vsqr_G * vsqr_G[:, np.newaxis]
chi_GG = np.dot(
np.linalg.inv(np.eye(nG) - np.dot(chi0_GG, K_GG)), chi0_GG)
if not return_VchiV:
chi0_GG /= vsqr_G * vsqr_G[:, np.newaxis]
chi_GG /= vsqr_G * vsqr_G[:, np.newaxis]
chi_wGG.append(chi_GG)
if len(chi_wGG):
chi_wGG = np.array(chi_wGG)
else:
chi_wGG = np.zeros((0, nG, nG), complex)
# Spin response
else:
Kxc_GG = get_xc_kernel(pd,
self.chi0,
functional=xc,
kernel=response[::-1],
RSrep=RSrep,
chi0_wGG=chi0_wGG,
fxc_scaling=fxc_scaling,
density_cut=density_cut,
spinpol_cut=spinpol_cut)
# Invert Dyson equation
chi_wGG = []
for chi0_GG in chi0_wGG:
chi_GG = np.dot(
np.linalg.inv(
np.eye(len(chi0_GG)) - np.dot(chi0_GG, Kxc_GG)),
chi0_GG)
chi_wGG.append(chi_GG)
return pd, chi0_wGG, np.array(chi_wGG)