def gf_k(interfaces, parent, ps, qs, kwargs, return_ncalls=False):
"""K-dependent Green's function."""
ncalls = 0
result_gf = []
log = interfaces[0].logger
log.note("Starting a K-GF calculation n_k = {:d}".format(
len(interfaces), ))
ps = np.array(ps)
qs = np.array(qs)
for interface in interfaces:
log.note("Running K-GF @ id(k)={:d} ...".format(len(result_gf)))
idx = padding_k_idx(interface.cc, kind="joint")[interface.k]
ps_physical = np.any(ps[:, np.newaxis] == idx[np.newaxis, :], axis=1)
qs_physical = np.any(qs[:, np.newaxis] == idx[np.newaxis, :], axis=1)
kwargs.update(
dict(
return_ncalls=return_ncalls,
interface=interface,
ps=ps[ps_physical],
qs=qs[qs_physical],
))
result = parent(**kwargs)
if return_ncalls:
ncalls += result[1]
result = result[0]
result_gf.append(result)
gfvals = np.array(result_gf)
if return_ncalls:
return gfvals, ncalls
else:
return gfvals
def init_amps(self, eris):
time0 = time.clock(), time.time()
nocc = self.nocc
nvir = self.nmo - nocc
nkpts = self.nkpts
t1 = np.zeros((nkpts, nocc, nvir), dtype=eris.fock.dtype)
t2 = np.empty((nkpts, nkpts, nkpts, nocc, nocc, nvir, nvir),
dtype=eris.fock.dtype)
mo_e_o = [eris.mo_energy[k][:nocc] for k in range(nkpts)]
mo_e_v = [eris.mo_energy[k][nocc:] for k in range(nkpts)]
# Get location of padded elements in occupied and virtual space
nonzero_opadding, nonzero_vpadding = padding_k_idx(self, kind="split")
emp2 = 0
kconserv = self.khelper.kconserv
touched = np.zeros((nkpts, nkpts, nkpts), dtype=bool)
for ki, kj, ka in kpts_helper.loop_kkk(nkpts):
if touched[ki, kj, ka]:
continue
kb = kconserv[ki, ka, kj]
# For discussion of LARGE_DENOM, see t1new update above
eia = LARGE_DENOM * np.ones(
(nocc, nvir), dtype=eris.mo_energy[0].dtype)
n0_ovp_ia = np.ix_(nonzero_opadding[ki], nonzero_vpadding[ka])
eia[n0_ovp_ia] = (mo_e_o[ki][:, None] - mo_e_v[ka])[n0_ovp_ia]
ejb = LARGE_DENOM * np.ones(
(nocc, nvir), dtype=eris.mo_energy[0].dtype)
n0_ovp_jb = np.ix_(nonzero_opadding[kj], nonzero_vpadding[kb])
ejb[n0_ovp_jb] = (mo_e_o[kj][:, None] - mo_e_v[kb])[n0_ovp_jb]
eijab = eia[:, None, :, None] + ejb[:, None, :]
eris_ijab = eris.oovv[ki, kj, ka]
eris_ijba = eris.oovv[ki, kj, kb]
t2[ki, kj, ka] = eris_ijab.conj() / eijab
woovv = 2 * eris_ijab - eris_ijba.transpose(0, 1, 3, 2)
emp2 += np.einsum('ijab,ijab', t2[ki, kj, ka], woovv)
if ka != kb:
eijba = eijab.transpose(0, 1, 3, 2)
t2[ki, kj, kb] = eris_ijba.conj() / eijba
woovv = 2 * eris_ijba - eris_ijab.transpose(0, 1, 3, 2)
emp2 += np.einsum('ijab,ijab', t2[ki, kj, kb], woovv)
touched[ki, kj, ka] = touched[ki, kj, kb] = True
self.emp2 = emp2.real / nkpts
logger.info(
self, 'Init t2, MP2 energy (with fock eigenvalue shift) = %.15g',
self.emp2)
logger.timer(self, 'init mp2', *time0)
return self.emp2, t1, t2
def iter_12(cc, k):
"""Iterates over IP index slices."""
o, v = padding_k_idx(cc, kind="split")
kconserv = cc.khelper.kconserv
yield (o[k],)
for ki in range(cc.nkpts):
for kj in range(cc.nkpts):
kb = kconserv[ki, k, kj]
yield (ki,), (kj,), o[ki], o[kj], v[kb]
def iter_12(cc, k):
"""Iterates over EA index slices."""
o, v = padding_k_idx(cc, kind="split")
kconserv = cc.khelper.kconserv
yield (v[k], )
for ki in range(cc.nkpts):
for ka in range(cc.nkpts):
kb = kconserv[k, ka, ki]
yield (ki, ), (ka, ), o[ki], v[ka], v[kb]
def iter_12(cc_or_eom, k):
"""Iterates over IP index slices."""
if isinstance(cc_or_eom, kccsd_rhf.RCCSD):
cc = cc_or_eom
else:
cc = cc_or_eom._cc
o, v = padding_k_idx(cc, kind="split")
kconserv = cc.khelper.kconserv
yield (o[k],)
for ki in range(cc.nkpts):
for kj in range(cc.nkpts):
kb = kconserv[ki, k, kj]
yield (ki,), (kj,), o[ki], o[kj], v[kb]
def init_amps(self, eris):
time0 = time.clock(), time.time()
nocc = self.nocc
nvir = self.nmo - nocc
nkpts = self.nkpts
mo_e_o = [eris.mo_energy[k][:nocc] for k in range(nkpts)]
mo_e_v = [eris.mo_energy[k][nocc:] for k in range(nkpts)]
t1 = numpy.zeros((nkpts, nocc, nvir), dtype=numpy.complex128)
t2 = numpy.zeros((nkpts, nkpts, nkpts, nocc, nocc, nvir, nvir),
dtype=numpy.complex128)
self.emp2 = 0
foo = eris.fock[:, :nocc, :nocc].copy()
fvv = eris.fock[:, nocc:, nocc:].copy()
fov = eris.fock[:, :nocc, nocc:].copy()
eris_oovv = eris.oovv.copy()
# Get location of padded elements in occupied and virtual space
nonzero_opadding, nonzero_vpadding = padding_k_idx(self, kind="split")
kconserv = kpts_helper.get_kconserv(self._scf.cell, self.kpts)
for ki, kj, ka in kpts_helper.loop_kkk(nkpts):
kb = kconserv[ki, ka, kj]
# For LARGE_DENOM, see t1new update above
eia = LARGE_DENOM * numpy.ones(
(nocc, nvir), dtype=eris.mo_energy[0].dtype)
n0_ovp_ia = numpy.ix_(nonzero_opadding[ki], nonzero_vpadding[ka])
eia[n0_ovp_ia] = (mo_e_o[ki][:, None] - mo_e_v[ka])[n0_ovp_ia]
ejb = LARGE_DENOM * numpy.ones(
(nocc, nvir), dtype=eris.mo_energy[0].dtype)
n0_ovp_jb = numpy.ix_(nonzero_opadding[kj], nonzero_vpadding[kb])
ejb[n0_ovp_jb] = (mo_e_o[kj][:, None] - mo_e_v[kb])[n0_ovp_jb]
eijab = eia[:, None, :, None] + ejb[:, None, :]
t2[ki, kj, ka] = eris_oovv[ki, kj, ka] / eijab
t2 = numpy.conj(t2)
self.emp2 = 0.25 * numpy.einsum('pqrijab,pqrijab', t2, eris_oovv).real
self.emp2 /= nkpts
logger.info(self, 'Init t2, MP2 energy = %.15g', self.emp2.real)
logger.timer(self, 'init mp2', *time0)
return self.emp2, t1, t2
def mask_frozen(cc, vector, k, const=LARGE_DENOM):
'''Replaces all frozen orbital indices of `vector` with the value `const`.'''
r1, r2 = vector_to_amplitudes(cc, vector, k)
nkpts, nocc, nvir = cc.t1.shape
kconserv = cc.khelper.kconserv
# Get location of padded elements in occupied and virtual space
nonzero_opadding, nonzero_vpadding = padding_k_idx(cc, kind="split")
new_r1 = const * np.ones_like(r1)
new_r2 = const * np.ones_like(r2)
new_r1[nonzero_opadding[k]] = r1[nonzero_opadding[k]]
for ki in range(nkpts):
for kj in range(nkpts):
kb = kconserv[ki, k, kj]
idx = np.ix_([ki], [kj], nonzero_opadding[ki], nonzero_opadding[kj], nonzero_vpadding[kb])
new_r2[idx] = r2[idx]
return amplitudes_to_vector(cc, new_r1, new_r2, k)
def init_amps(self, eris):
time0 = time.clock(), time.time()
nocc = self.nocc
nvir = self.nmo - nocc
nkpts = self.nkpts
mo_e_o = [eris.mo_energy[k][:nocc] for k in range(nkpts)]
mo_e_v = [eris.mo_energy[k][nocc:] for k in range(nkpts)]
t1 = numpy.zeros((nkpts, nocc, nvir), dtype=numpy.complex128)
t2 = numpy.zeros((nkpts, nkpts, nkpts, nocc, nocc, nvir, nvir), dtype=numpy.complex128)
self.emp2 = 0
foo = eris.fock[:, :nocc, :nocc].copy()
fvv = eris.fock[:, nocc:, nocc:].copy()
fov = eris.fock[:, :nocc, nocc:].copy()
eris_oovv = eris.oovv.copy()
# Get location of padded elements in occupied and virtual space
nonzero_opadding, nonzero_vpadding = padding_k_idx(self, kind="split")
kconserv = kpts_helper.get_kconserv(self._scf.cell, self.kpts)
for ki, kj, ka in kpts_helper.loop_kkk(nkpts):
kb = kconserv[ki, ka, kj]
# For LARGE_DENOM, see t1new update above
eia = LARGE_DENOM * numpy.ones((nocc, nvir), dtype=eris.mo_energy[0].dtype)
n0_ovp_ia = numpy.ix_(nonzero_opadding[ki], nonzero_vpadding[ka])
eia[n0_ovp_ia] = (mo_e_o[ki][:,None] - mo_e_v[ka])[n0_ovp_ia]
ejb = LARGE_DENOM * numpy.ones((nocc, nvir), dtype=eris.mo_energy[0].dtype)
n0_ovp_jb = numpy.ix_(nonzero_opadding[kj], nonzero_vpadding[kb])
ejb[n0_ovp_jb] = (mo_e_o[kj][:,None] - mo_e_v[kb])[n0_ovp_jb]
eijab = eia[:, None, :, None] + ejb[:, None, :]
t2[ki, kj, ka] = eris_oovv[ki, kj, ka] / eijab
t2 = numpy.conj(t2)
self.emp2 = 0.25 * numpy.einsum('pqrijab,pqrijab', t2, eris_oovv).real
self.emp2 /= nkpts
logger.info(self, 'Init t2, MP2 energy = %.15g', self.emp2.real)
logger.timer(self, 'init mp2', *time0)
return self.emp2, t1, t2
def kernel(mycc, eris, t1=None, t2=None, max_memory=2000, verbose=logger.INFO):
'''Returns the CCSD(T) for general spin-orbital integrals with k-points.
Note:
Returns real part of the CCSD(T) energy, raises warning if there is
a complex part.
Args:
mycc (:class:`GCCSD`): Coupled-cluster object storing results of
a coupled-cluster calculation.
eris (:class:`_ERIS`): Integral object holding the relevant electron-
repulsion integrals and Fock matrix elements
t1 (:obj:`ndarray`): t1 coupled-cluster amplitudes
t2 (:obj:`ndarray`): t2 coupled-cluster amplitudes
max_memory (float): Maximum memory used in calculation (NOT USED)
verbose (int, :class:`Logger`): verbosity of calculation
Returns:
energy_t (float): The real-part of the k-point CCSD(T) energy.
'''
assert isinstance(mycc, pyscf.pbc.cc.kccsd.GCCSD)
if isinstance(verbose, logger.Logger):
log = verbose
else:
log = logger.Logger(mycc.stdout, verbose)
if t1 is None: t1 = mycc.t1
if t2 is None: t2 = mycc.t2
if t1 is None or t2 is None:
raise TypeError(
'Must pass in t1/t2 amplitudes to k-point CCSD(T)! (Maybe '
'need to run `.ccsd()` on the ccsd object?)')
cell = mycc._scf.cell
kpts = mycc.kpts
# The dtype of any local arrays that will be created
dtype = t1.dtype
nkpts, nocc, nvir = t1.shape
mo_energy_occ = [eris.mo_energy[ki][:nocc] for ki in range(nkpts)]
mo_energy_vir = [eris.mo_energy[ki][nocc:] for ki in range(nkpts)]
fov = eris.fock[:, :nocc, nocc:]
mo_e_o = mo_energy_occ
mo_e_v = mo_energy_vir
# Set up class for k-point conservation
kconserv = kpts_helper.get_kconserv(cell, kpts)
# Get location of padded elements in occupied and virtual space
nonzero_opadding, nonzero_vpadding = padding_k_idx(mycc, kind="split")
energy_t = 0.0
for ki in range(nkpts):
for kj in range(ki + 1):
for kk in range(kj + 1):
# eigenvalue denominator: e(i) + e(j) + e(k)
eijk = _get_epqr([0, nocc, ki, mo_e_o, nonzero_opadding],
[0, nocc, kj, mo_e_o, nonzero_opadding],
[0, nocc, kk, mo_e_o, nonzero_opadding])
# Factors to include for permutational symmetry among k-points for occupied space
if ki == kj and kj == kk:
symm_ijk_kpt = 1. # only one degeneracy
elif ki == kj or kj == kk:
symm_ijk_kpt = 3. # 3 degeneracies when only one k-point is unique
else:
symm_ijk_kpt = 6. # 3! combinations of arranging 3 distinct k-points
for ka in range(nkpts):
for kb in range(ka + 1):
# Find momentum conservation condition for triples
# amplitude t3ijkabc
kc = kpts_helper.get_kconserv3(cell, kpts,
[ki, kj, kk, ka, kb])
if kc not in range(kb + 1):
continue
# -1.0 so the LARGE_DENOM does not cancel with the one from eijk
eabc = _get_epqr(
[0, nvir, ka, mo_e_v, nonzero_vpadding],
[0, nvir, kb, mo_e_v, nonzero_vpadding],
[0, nvir, kc, mo_e_v, nonzero_vpadding],
fac=[-1., -1., -1.])
# Factors to include for permutational symmetry among k-points for virtual space
if ka == kb and kb == kc:
symm_abc_kpt = 1. # one unique combination of (ka, kb, kc)
elif ka == kb or kb == kc:
symm_abc_kpt = 3. # 3 unique combinations of (ka, kb, kc)
else:
symm_abc_kpt = 6. # 6 unique combinations of (ka, kb, kc)
# Determine the a, b, c indices we will loop over as
# determined by the k-point symmetry.
abc_indices = cartesian_prod([range(nvir)] * 3)
symm_3d = symm_2d_ab = symm_2d_bc = False
if ka == kc: # == kb from lower triangular summation
abc_indices = tril_product(
range(nvir), repeat=3,
tril_idx=[0, 1, 2]) # loop a >= b >= c
symm_3d = True
elif ka == kb:
abc_indices = tril_product(
range(nvir), repeat=3,
tril_idx=[0, 1]) # loop a >= b
symm_2d_ab = True
elif kb == kc:
abc_indices = tril_product(
range(nvir), repeat=3,
tril_idx=[1, 2]) # loop b >= c
symm_2d_bc = True
for a, b, c in abc_indices:
# See symm_3d and abc_indices above for description of factors
symm_abc = 1.
if symm_3d:
if a == b == c:
symm_abc = 1.
elif a == b or b == c:
symm_abc = 3.
else:
symm_abc = 6.
elif symm_2d_ab:
if a == b:
symm_abc = 1.
else:
symm_abc = 2.
elif symm_2d_bc:
if b == c:
symm_abc = 1.
else:
symm_abc = 2.
# Form energy denominator
eijkabc = (eijk[:, :, :] + eabc[a, b, c])
# Form connected triple excitation amplitude
t3c = np.zeros((nocc, nocc, nocc), dtype=dtype)
# First term: 1 - p(ij) - p(ik)
ke = kconserv[kj, ka, kk]
t3c = t3c + einsum(
'jke,ie->ijk', t2[kj, kk, ka, :, :, a, :],
-eris.ovvv[ki, ke, kc, :, :, c, b].conj())
ke = kconserv[ki, ka, kk]
t3c = t3c - einsum(
'ike,je->ijk', t2[ki, kk, ka, :, :, a, :],
-eris.ovvv[kj, ke, kc, :, :, c, b].conj())
ke = kconserv[kj, ka, ki]
t3c = t3c - einsum(
'jie,ke->ijk', t2[kj, ki, ka, :, :, a, :],
-eris.ovvv[kk, ke, kc, :, :, c, b].conj())
km = kconserv[kb, ki, kc]
t3c = t3c - einsum(
'mi,jkm->ijk', t2[km, ki, kb, :, :, b, c],
eris.ooov[kj, kk, km, :, :, :, a].conj())
km = kconserv[kb, kj, kc]
t3c = t3c + einsum(
'mj,ikm->ijk', t2[km, kj, kb, :, :, b, c],
eris.ooov[ki, kk, km, :, :, :, a].conj())
km = kconserv[kb, kk, kc]
t3c = t3c + einsum(
'mk,jim->ijk', t2[km, kk, kb, :, :, b, c],
eris.ooov[kj, ki, km, :, :, :, a].conj())
# Second term: - p(ab) + p(ab) p(ij) + p(ab) p(ik)
ke = kconserv[kj, kb, kk]
t3c = t3c - einsum(
'jke,ie->ijk', t2[kj, kk, kb, :, :, b, :],
-eris.ovvv[ki, ke, kc, :, :, c, a].conj())
ke = kconserv[ki, kb, kk]
t3c = t3c + einsum(
'ike,je->ijk', t2[ki, kk, kb, :, :, b, :],
-eris.ovvv[kj, ke, kc, :, :, c, a].conj())
ke = kconserv[kj, kb, ki]
t3c = t3c + einsum(
'jie,ke->ijk', t2[kj, ki, kb, :, :, b, :],
-eris.ovvv[kk, ke, kc, :, :, c, a].conj())
km = kconserv[ka, ki, kc]
t3c = t3c + einsum(
'mi,jkm->ijk', t2[km, ki, ka, :, :, a, c],
eris.ooov[kj, kk, km, :, :, :, b].conj())
km = kconserv[ka, kj, kc]
t3c = t3c - einsum(
'mj,ikm->ijk', t2[km, kj, ka, :, :, a, c],
eris.ooov[ki, kk, km, :, :, :, b].conj())
km = kconserv[ka, kk, kc]
t3c = t3c - einsum(
'mk,jim->ijk', t2[km, kk, ka, :, :, a, c],
eris.ooov[kj, ki, km, :, :, :, b].conj())
# Third term: - p(ac) + p(ac) p(ij) + p(ac) p(ik)
ke = kconserv[kj, kc, kk]
t3c = t3c - einsum(
'jke,ie->ijk', t2[kj, kk, kc, :, :, c, :],
-eris.ovvv[ki, ke, ka, :, :, a, b].conj())
ke = kconserv[ki, kc, kk]
t3c = t3c + einsum(
'ike,je->ijk', t2[ki, kk, kc, :, :, c, :],
-eris.ovvv[kj, ke, ka, :, :, a, b].conj())
ke = kconserv[kj, kc, ki]
t3c = t3c + einsum(
'jie,ke->ijk', t2[kj, ki, kc, :, :, c, :],
-eris.ovvv[kk, ke, ka, :, :, a, b].conj())
km = kconserv[kb, ki, ka]
t3c = t3c + einsum(
'mi,jkm->ijk', t2[km, ki, kb, :, :, b, a],
eris.ooov[kj, kk, km, :, :, :, c].conj())
km = kconserv[kb, kj, ka]
t3c = t3c - einsum(
'mj,ikm->ijk', t2[km, kj, kb, :, :, b, a],
eris.ooov[ki, kk, km, :, :, :, c].conj())
km = kconserv[kb, kk, ka]
t3c = t3c - einsum(
'mk,jim->ijk', t2[km, kk, kb, :, :, b, a],
eris.ooov[kj, ki, km, :, :, :, c].conj())
# Form disconnected triple excitation amplitude contribution
t3d = np.zeros((nocc, nocc, nocc), dtype=dtype)
# First term: 1 - p(ij) - p(ik)
if ki == ka:
t3d = t3d + einsum(
'i,jk->ijk', t1[ki, :, a],
-eris.oovv[kj, kk, kb, :, :, b, c].conj())
t3d = t3d + einsum('i,jk->ijk', -fov[ki, :, a],
t2[kj, kk, kb, :, :, b, c])
if kj == ka:
t3d = t3d - einsum(
'j,ik->ijk', t1[kj, :, a],
-eris.oovv[ki, kk, kb, :, :, b, c].conj())
t3d = t3d - einsum('j,ik->ijk', -fov[kj, :, a],
t2[ki, kk, kb, :, :, b, c])
if kk == ka:
t3d = t3d - einsum(
'k,ji->ijk', t1[kk, :, a],
-eris.oovv[kj, ki, kb, :, :, b, c].conj())
t3d = t3d - einsum('k,ji->ijk', -fov[kk, :, a],
t2[kj, ki, kb, :, :, b, c])
# Second term: - p(ab) + p(ab) p(ij) + p(ab) p(ik)
if ki == kb:
t3d = t3d - einsum(
'i,jk->ijk', t1[ki, :, b],
-eris.oovv[kj, kk, ka, :, :, a, c].conj())
t3d = t3d - einsum('i,jk->ijk', -fov[ki, :, b],
t2[kj, kk, ka, :, :, a, c])
if kj == kb:
t3d = t3d + einsum(
'j,ik->ijk', t1[kj, :, b],
-eris.oovv[ki, kk, ka, :, :, a, c].conj())
t3d = t3d + einsum('j,ik->ijk', -fov[kj, :, b],
t2[ki, kk, ka, :, :, a, c])
if kk == kb:
t3d = t3d + einsum(
'k,ji->ijk', t1[kk, :, b],
-eris.oovv[kj, ki, ka, :, :, a, c].conj())
t3d = t3d + einsum('k,ji->ijk', -fov[kk, :, b],
t2[kj, ki, ka, :, :, a, c])
# Third term: - p(ac) + p(ac) p(ij) + p(ac) p(ik)
if ki == kc:
t3d = t3d - einsum(
'i,jk->ijk', t1[ki, :, c],
-eris.oovv[kj, kk, kb, :, :, b, a].conj())
t3d = t3d - einsum('i,jk->ijk', -fov[ki, :, c],
t2[kj, kk, kb, :, :, b, a])
if kj == kc:
t3d = t3d + einsum(
'j,ik->ijk', t1[kj, :, c],
-eris.oovv[ki, kk, kb, :, :, b, a].conj())
t3d = t3d + einsum('j,ik->ijk', -fov[kj, :, c],
t2[ki, kk, kb, :, :, b, a])
if kk == kc:
t3d = t3d + einsum(
'k,ji->ijk', t1[kk, :, c],
-eris.oovv[kj, ki, kb, :, :, b, a].conj())
t3d = t3d + einsum('k,ji->ijk', -fov[kk, :, c],
t2[kj, ki, kb, :, :, b, a])
t3c_plus_d = t3c + t3d
t3c_plus_d /= eijkabc
energy_t += symm_abc_kpt * symm_ijk_kpt * symm_abc * einsum(
'ijk,ijk', t3c, t3c_plus_d.conj())
energy_t = (1. / 36) * energy_t / nkpts
if abs(energy_t.imag) > 1e-4:
log.warn('Non-zero imaginary part of CCSD(T) energy was found %s',
energy_t.imag)
log.note('CCSD(T) correction per cell = %.15g', energy_t.real)
return energy_t.real
def get_padding_k_idx(self, cc):
return padding_k_idx(cc, kind='split')
def get_t3p2_imds_slow(cc,
t1,
t2,
eris=None,
t3p2_ip_out=None,
t3p2_ea_out=None):
"""For a description of arguments, see `get_t3p2_imds_slow` in
the corresponding `kintermediates.py`.
"""
from pyscf.pbc.cc.kccsd_t_rhf import _get_epqr
if eris is None:
eris = cc.ao2mo()
fock = eris.fock
nkpts, nocc, nvir = t1.shape
kconserv = cc.khelper.kconserv
dtype = np.result_type(t1, t2)
fov = fock[:, :nocc, nocc:]
#foo = [fock[ikpt, :nocc, :nocc].diagonal() for ikpt in range(nkpts)]
#fvv = [fock[ikpt, nocc:, nocc:].diagonal() for ikpt in range(nkpts)]
mo_energy_occ = np.array(
[eris.mo_energy[ki][:nocc] for ki in range(nkpts)])
mo_energy_vir = np.array(
[eris.mo_energy[ki][nocc:] for ki in range(nkpts)])
mo_e_o = mo_energy_occ
mo_e_v = mo_energy_vir
# Get location of padded elements in occupied and virtual space
nonzero_opadding, nonzero_vpadding = padding_k_idx(cc, kind="split")
ccsd_energy = cc.energy(t1, t2, eris)
if t3p2_ip_out is None:
t3p2_ip_out = np.zeros((nkpts, nkpts, nkpts, nocc, nvir, nocc, nocc),
dtype=dtype)
Wmcik = t3p2_ip_out
if t3p2_ea_out is None:
t3p2_ea_out = np.zeros((nkpts, nkpts, nkpts, nvir, nvir, nvir, nocc),
dtype=dtype)
Wacek = t3p2_ea_out
from itertools import product
tmp_t3 = np.empty((nkpts, nkpts, nkpts, nkpts, nkpts, nocc, nocc, nocc,
nvir, nvir, nvir),
dtype=t2.dtype)
def get_w(ki, kj, kk, ka, kb, kc):
kf = kconserv[ka, ki, kb]
ret = lib.einsum('fiba,kjcf->ijkabc', eris.vovv[kf, ki, kb].conj(),
t2[kk, kj, kc])
km = kconserv[kc, kk, kb]
ret -= lib.einsum('jima,mkbc->ijkabc', eris.ooov[kj, ki, km].conj(),
t2[km, kk, kb])
return ret
for ki, kj, kk, ka, kb in product(range(nkpts), repeat=5):
kc = kpts_helper.get_kconserv3(cc._scf.cell, cc.kpts,
[ki, kj, kk, ka, kb])
tmp_t3[ki, kj, kk, ka, kb] = get_w(ki, kj, kk, ka, kb, kc)
tmp_t3[ki, kj, kk, ka, kb] += get_w(ki, kk, kj, ka, kc,
kb).transpose(0, 2, 1, 3, 5, 4)
tmp_t3[ki, kj, kk, ka, kb] += get_w(kj, ki, kk, kb, ka,
kc).transpose(1, 0, 2, 4, 3, 5)
tmp_t3[ki, kj, kk, ka, kb] += get_w(kj, kk, ki, kb, kc,
ka).transpose(2, 0, 1, 5, 3, 4)
tmp_t3[ki, kj, kk, ka, kb] += get_w(kk, ki, kj, kc, ka,
kb).transpose(1, 2, 0, 4, 5, 3)
tmp_t3[ki, kj, kk, ka, kb] += get_w(kk, kj, ki, kc, kb,
ka).transpose(2, 1, 0, 5, 4, 3)
eijk = _get_epqr([0, nocc, ki, mo_e_o, nonzero_opadding],
[0, nocc, kj, mo_e_o, nonzero_opadding],
[0, nocc, kk, mo_e_o, nonzero_opadding])
eabc = _get_epqr([0, nvir, ka, mo_e_v, nonzero_vpadding],
[0, nvir, kb, mo_e_v, nonzero_vpadding],
[0, nvir, kc, mo_e_v, nonzero_vpadding],
fac=[-1., -1., -1.])
eijkabc = eijk[:, :, :, None, None, None] + eabc[None, None,
None, :, :, :]
tmp_t3[ki, kj, kk, ka, kb] /= eijkabc
pt1 = np.zeros((nkpts, nocc, nvir), dtype=t2.dtype)
for ki in range(nkpts):
for km, kn, ke in product(range(nkpts), repeat=3):
kf = kconserv[km, ke, kn]
Soovv = 2. * eris.oovv[km, kn, ke] - eris.oovv[km, kn,
kf].transpose(
0, 1, 3, 2)
St3 = (tmp_t3[ki, km, kn, ki, ke] -
tmp_t3[ki, km, kn, ke, ki].transpose(0, 1, 2, 4, 3, 5))
pt1[ki] += lib.einsum('mnef,imnaef->ia', Soovv, St3)
pt2 = np.zeros((nkpts, nkpts, nkpts, nocc, nocc, nvir, nvir),
dtype=t2.dtype)
for ki, kj, ka in product(range(nkpts), repeat=3):
kb = kconserv[ki, ka, kj]
for km in range(nkpts):
for kn in range(nkpts):
# (ia,jb) -> (ia,jb)
ke = kconserv[km, kj, kn]
pt2[ki, kj, ka] += -2. * lib.einsum(
'imnabe,mnje->ijab', tmp_t3[ki, km, kn, ka,
kb], eris.ooov[km, kn, kj])
pt2[ki, kj, ka] += lib.einsum('imnabe,nmje->ijab',
tmp_t3[ki, km, kn, ka, kb],
eris.ooov[kn, km, kj])
pt2[ki, kj, ka] += lib.einsum('inmeab,mnje->ijab',
tmp_t3[ki, kn, km, ke, ka],
eris.ooov[km, kn, kj])
# (ia,jb) -> (jb,ia)
ke = kconserv[km, ki, kn]
pt2[ki, kj, ka] += -2. * lib.einsum(
'jmnbae,mnie->ijab', tmp_t3[kj, km, kn, kb,
ka], eris.ooov[km, kn, ki])
pt2[ki, kj, ka] += lib.einsum('jmnbae,nmie->ijab',
tmp_t3[kj, km, kn, kb, ka],
eris.ooov[kn, km, ki])
pt2[ki, kj, ka] += lib.einsum('jnmeba,mnie->ijab',
tmp_t3[kj, kn, km, ke, kb],
eris.ooov[km, kn, ki])
# (ia,jb) -> (ia,jb)
pt2[ki, kj, ka] += lib.einsum('ijmabe,me->ijab',
tmp_t3[ki, kj, km, ka, kb], fov[km])
pt2[ki, kj, ka] -= lib.einsum('ijmaeb,me->ijab',
tmp_t3[ki, kj, km, ka, km], fov[km])
# (ia,jb) -> (jb,ia)
pt2[ki, kj, ka] += lib.einsum('jimbae,me->ijab',
tmp_t3[kj, ki, km, kb, ka], fov[km])
pt2[ki, kj, ka] -= lib.einsum('jimbea,me->ijab',
tmp_t3[kj, ki, km, kb, km], fov[km])
for ke in range(nkpts):
# (ia,jb) -> (ia,jb)
kf = kconserv[km, ke, kb]
pt2[ki, kj, ka] += 2. * lib.einsum(
'ijmaef,bmef->ijab', tmp_t3[ki, kj, km, ka,
ke], eris.vovv[kb, km, ke])
pt2[ki, kj, ka] -= lib.einsum('ijmaef,bmfe->ijab',
tmp_t3[ki, kj, km, ka, ke],
eris.vovv[kb, km, kf])
pt2[ki, kj, ka] -= lib.einsum('imjfae,bmef->ijab',
tmp_t3[ki, km, kj, kf, ka],
eris.vovv[kb, km, ke])
# (ia,jb) -> (jb,ia)
kf = kconserv[km, ke, ka]
pt2[ki, kj, ka] += 2. * lib.einsum(
'jimbef,amef->ijab', tmp_t3[kj, ki, km, kb,
ke], eris.vovv[ka, km, ke])
pt2[ki, kj, ka] -= lib.einsum('jimbef,amfe->ijab',
tmp_t3[kj, ki, km, kb, ke],
eris.vovv[ka, km, kf])
pt2[ki, kj, ka] -= lib.einsum('jmifbe,amef->ijab',
tmp_t3[kj, km, ki, kf, kb],
eris.vovv[ka, km, ke])
for ki in range(nkpts):
ka = ki
eia = LARGE_DENOM * np.ones(
(nocc, nvir), dtype=eris.mo_energy[0].dtype)
n0_ovp_ia = np.ix_(nonzero_opadding[ki], nonzero_vpadding[ka])
eia[n0_ovp_ia] = (mo_e_o[ki][:, None] - mo_e_v[ka])[n0_ovp_ia]
pt1[ki] /= eia
for ki, ka in product(range(nkpts), repeat=2):
eia = LARGE_DENOM * np.ones(
(nocc, nvir), dtype=eris.mo_energy[0].dtype)
n0_ovp_ia = np.ix_(nonzero_opadding[ki], nonzero_vpadding[ka])
eia[n0_ovp_ia] = (mo_e_o[ki][:, None] - mo_e_v[ka])[n0_ovp_ia]
for kj in range(nkpts):
kb = kconserv[ki, ka, kj]
ejb = LARGE_DENOM * np.ones(
(nocc, nvir), dtype=eris.mo_energy[0].dtype)
n0_ovp_jb = np.ix_(nonzero_opadding[kj], nonzero_vpadding[kb])
ejb[n0_ovp_jb] = (mo_e_o[kj][:, None] - mo_e_v[kb])[n0_ovp_jb]
eijab = eia[:, None, :, None] + ejb[:, None, :]
pt2[ki, kj, ka] /= eijab
pt1 += t1
pt2 += t2
for ki, kj, kk, ka, kb in product(range(nkpts), repeat=5):
kc = kpts_helper.get_kconserv3(cc._scf.cell, cc.kpts,
[ki, kj, kk, ka, kb])
km = kconserv[kc, ki, ka]
_oovv = eris.oovv[km, ki, kc]
Wmcik[km, kb, kk] += 2. * lib.einsum('ijkabc,mica->mbkj',
tmp_t3[ki, kj, kk, ka, kb], _oovv)
Wmcik[km, kb, kk] -= lib.einsum('jikabc,mica->mbkj',
tmp_t3[kj, ki, kk, ka, kb], _oovv)
Wmcik[km, kb, kk] -= lib.einsum('kjiabc,mica->mbkj',
tmp_t3[kk, kj, ki, ka, kb], _oovv)
for ki, kj, kk, ka, kb in product(range(nkpts), repeat=5):
kc = kpts_helper.get_kconserv3(cc._scf.cell, cc.kpts,
[ki, kj, kk, ka, kb])
ke = kconserv[ki, ka, kk]
_oovv = eris.oovv[ki, kk, ka]
Wacek[kc, kb, ke] -= 2. * lib.einsum('ijkabc,ikae->cbej',
tmp_t3[ki, kj, kk, ka, kb], _oovv)
Wacek[kc, kb, ke] += lib.einsum('jikabc,ikae->cbej',
tmp_t3[kj, ki, kk, ka, kb], _oovv)
Wacek[kc, kb, ke] += lib.einsum('kjiabc,ikae->cbej',
tmp_t3[kk, kj, ki, ka, kb], _oovv)
delta_ccsd_energy = cc.energy(pt1, pt2, eris) - ccsd_energy
lib.logger.info(cc, 'CCSD energy T3[2] correction : %16.12e',
delta_ccsd_energy)
return delta_ccsd_energy, pt1, pt2, Wmcik, Wacek
def update_amps(cc, t1, t2, eris):
time0 = time1 = time.clock(), time.time()
log = logger.Logger(cc.stdout, cc.verbose)
nkpts, nocc, nvir = t1.shape
fock = eris.fock
mo_e_o = [e[:nocc] for e in eris.mo_energy]
mo_e_v = [e[nocc:] + cc.level_shift for e in eris.mo_energy]
# Get location of padded elements in occupied and virtual space
nonzero_opadding, nonzero_vpadding = padding_k_idx(cc, kind="split")
fov = fock[:, :nocc, nocc:]
foo = fock[:, :nocc, :nocc]
fvv = fock[:, nocc:, nocc:]
kconserv = cc.khelper.kconserv
Foo = imdk.cc_Foo(t1, t2, eris, kconserv)
Fvv = imdk.cc_Fvv(t1, t2, eris, kconserv)
Fov = imdk.cc_Fov(t1, t2, eris, kconserv)
Loo = imdk.Loo(t1, t2, eris, kconserv)
Lvv = imdk.Lvv(t1, t2, eris, kconserv)
# Move energy terms to the other side
for k in range(nkpts):
Foo[k][np.diag_indices(nocc)] -= mo_e_o[k]
Fvv[k][np.diag_indices(nvir)] -= mo_e_v[k]
Loo[k][np.diag_indices(nocc)] -= mo_e_o[k]
Lvv[k][np.diag_indices(nvir)] -= mo_e_v[k]
time1 = log.timer_debug1('intermediates', *time1)
# T1 equation
t1new = np.array(fov).astype(t1.dtype).conj()
for ka in range(nkpts):
ki = ka
# kc == ki; kk == ka
t1new[ka] += -2. * einsum('kc,ka,ic->ia', fov[ki], t1[ka], t1[ki])
t1new[ka] += einsum('ac,ic->ia', Fvv[ka], t1[ki])
t1new[ka] += -einsum('ki,ka->ia', Foo[ki], t1[ka])
tau_term = np.empty((nkpts, nocc, nocc, nvir, nvir), dtype=t1.dtype)
for kk in range(nkpts):
tau_term[kk] = 2 * t2[kk, ki, kk] - t2[ki, kk, kk].transpose(1, 0, 2, 3)
tau_term[ka] += einsum('ic,ka->kica', t1[ki], t1[ka])
for kk in range(nkpts):
kc = kk
t1new[ka] += einsum('kc,kica->ia', Fov[kc], tau_term[kk])
t1new[ka] += einsum('akic,kc->ia', 2 * eris.voov[ka, kk, ki], t1[kc])
t1new[ka] += einsum('kaic,kc->ia', -eris.ovov[kk, ka, ki], t1[kc])
for kc in range(nkpts):
kd = kconserv[ka, kc, kk]
Svovv = 2 * eris.vovv[ka, kk, kc] - eris.vovv[ka, kk, kd].transpose(0, 1, 3, 2)
tau_term_1 = t2[ki, kk, kc].copy()
if ki == kc and kk == kd:
tau_term_1 += einsum('ic,kd->ikcd', t1[ki], t1[kk])
t1new[ka] += einsum('akcd,ikcd->ia', Svovv, tau_term_1)
# kk - ki + kl = kc
# => kl = ki - kk + kc
kl = kconserv[ki, kk, kc]
Sooov = 2 * eris.ooov[kk, kl, ki] - eris.ooov[kl, kk, ki].transpose(1, 0, 2, 3)
tau_term_1 = t2[kk, kl, ka].copy()
if kk == ka and kl == kc:
tau_term_1 += einsum('ka,lc->klac', t1[ka], t1[kc])
t1new[ka] += -einsum('klic,klac->ia', Sooov, tau_term_1)
time1 = log.timer_debug1('t1', *time1)
# T2 equation
t2new = np.empty_like(t2)
for ki, kj, ka in kpts_helper.loop_kkk(nkpts):
t2new[ki, kj, ka] = eris.oovv[ki, kj, ka].conj()
mem_now = lib.current_memory()[0]
if (nocc ** 4 * nkpts ** 3) * 16 / 1e6 + mem_now < cc.max_memory * .9:
Woooo = imdk.cc_Woooo(t1, t2, eris, kconserv)
else:
fimd = lib.H5TmpFile()
Woooo = fimd.create_dataset('oooo', (nkpts, nkpts, nkpts, nocc, nocc, nocc, nocc), t1.dtype.char)
Woooo = imdk.cc_Woooo(t1, t2, eris, kconserv, Woooo)
for ki, kj, ka in kpts_helper.loop_kkk(nkpts):
# Chemist's notation for momentum conserving t2(ki,kj,ka,kb)
kb = kconserv[ki, ka, kj]
t2new_tmp = np.zeros((nocc, nocc, nvir, nvir), dtype=t2.dtype)
for kl in range(nkpts):
kk = kconserv[kj, kl, ki]
tau_term = t2[kk, kl, ka].copy()
if kl == kb and kk == ka:
tau_term += einsum('ic,jd->ijcd', t1[ka], t1[kb])
t2new_tmp += 0.5 * einsum('klij,klab->ijab', Woooo[kk, kl, ki], tau_term)
t2new[ki, kj, ka] += t2new_tmp
t2new[kj, ki, kb] += t2new_tmp.transpose(1, 0, 3, 2)
Woooo = None
fimd = None
time1 = log.timer_debug1('t2 oooo', *time1)
# einsum('abcd,ijcd->ijab', Wvvvv, tau)
add_vvvv_(cc, t2new, t1, t2, eris)
time1 = log.timer_debug1('t2 vvvv', *time1)
for ki, kj, ka in kpts_helper.loop_kkk(nkpts):
kb = kconserv[ki, ka, kj]
t2new_tmp = einsum('ac,ijcb->ijab', Lvv[ka], t2[ki, kj, ka])
t2new_tmp += einsum('ki,kjab->ijab', -Loo[ki], t2[ki, kj, ka])
kc = kconserv[ka, ki, kb]
tmp2 = np.asarray(eris.vovv[kc, ki, kb]).transpose(3, 2, 1, 0).conj() \
- einsum('kbic,ka->abic', eris.ovov[ka, kb, ki], t1[ka])
t2new_tmp += einsum('abic,jc->ijab', tmp2, t1[kj])
kk = kconserv[ki, ka, kj]
tmp2 = np.asarray(eris.ooov[kj, ki, kk]).transpose(3, 2, 1, 0).conj() \
+ einsum('akic,jc->akij', eris.voov[ka, kk, ki], t1[kj])
t2new_tmp -= einsum('akij,kb->ijab', tmp2, t1[kb])
t2new[ki, kj, ka] += t2new_tmp
t2new[kj, ki, kb] += t2new_tmp.transpose(1, 0, 3, 2)
mem_now = lib.current_memory()[0]
if (nocc ** 2 * nvir ** 2 * nkpts ** 3) * 16 / 1e6 * 2 + mem_now < cc.max_memory * .9:
Wvoov = imdk.cc_Wvoov(t1, t2, eris, kconserv)
Wvovo = imdk.cc_Wvovo(t1, t2, eris, kconserv)
else:
fimd = lib.H5TmpFile()
Wvoov = fimd.create_dataset('voov', (nkpts, nkpts, nkpts, nvir, nocc, nocc, nvir), t1.dtype.char)
Wvovo = fimd.create_dataset('vovo', (nkpts, nkpts, nkpts, nvir, nocc, nvir, nocc), t1.dtype.char)
Wvoov = imdk.cc_Wvoov(t1, t2, eris, kconserv, Wvoov)
Wvovo = imdk.cc_Wvovo(t1, t2, eris, kconserv, Wvovo)
for ki, kj, ka in kpts_helper.loop_kkk(nkpts):
kb = kconserv[ki, ka, kj]
t2new_tmp = np.zeros((nocc, nocc, nvir, nvir), dtype=t2.dtype)
for kk in range(nkpts):
kc = kconserv[ka, ki, kk]
tmp_voov = 2. * Wvoov[ka, kk, ki] - Wvovo[ka, kk, kc].transpose(0, 1, 3, 2)
t2new_tmp += einsum('akic,kjcb->ijab', tmp_voov, t2[kk, kj, kc])
kc = kconserv[ka, ki, kk]
t2new_tmp -= einsum('akic,kjbc->ijab', Wvoov[ka, kk, ki], t2[kk, kj, kb])
kc = kconserv[kk, ka, kj]
t2new_tmp -= einsum('bkci,kjac->ijab', Wvovo[kb, kk, kc], t2[kk, kj, ka])
t2new[ki, kj, ka] += t2new_tmp
t2new[kj, ki, kb] += t2new_tmp.transpose(1, 0, 3, 2)
Wvoov = Wvovo = None
fimd = None
time1 = log.timer_debug1('t2 voov', *time1)
for ki in range(nkpts):
ka = ki
# Remove zero/padded elements from denominator
eia = LARGE_DENOM * np.ones((nocc, nvir), dtype=eris.mo_energy[0].dtype)
n0_ovp_ia = np.ix_(nonzero_opadding[ki], nonzero_vpadding[ka])
eia[n0_ovp_ia] = (mo_e_o[ki][:,None] - mo_e_v[ka])[n0_ovp_ia]
t1new[ki] /= eia
for ki, kj, ka in kpts_helper.loop_kkk(nkpts):
kb = kconserv[ki, ka, kj]
# For LARGE_DENOM, see t1new update above
eia = LARGE_DENOM * np.ones((nocc, nvir), dtype=eris.mo_energy[0].dtype)
n0_ovp_ia = np.ix_(nonzero_opadding[ki], nonzero_vpadding[ka])
eia[n0_ovp_ia] = (mo_e_o[ki][:,None] - mo_e_v[ka])[n0_ovp_ia]
ejb = LARGE_DENOM * np.ones((nocc, nvir), dtype=eris.mo_energy[0].dtype)
n0_ovp_jb = np.ix_(nonzero_opadding[kj], nonzero_vpadding[kb])
ejb[n0_ovp_jb] = (mo_e_o[kj][:,None] - mo_e_v[kb])[n0_ovp_jb]
eijab = eia[:, None, :, None] + ejb[:, None, :]
t2new[ki, kj, ka] /= eijab
time0 = log.timer_debug1('update t1 t2', *time0)
return t1new, t2new
def __init__(self, cc, mo_coeff=None, method='incore'):
from pyscf.pbc import df
from pyscf.pbc import tools
from pyscf.pbc.cc.ccsd import _adjust_occ
log = logger.Logger(cc.stdout, cc.verbose)
cput0 = (time.clock(), time.time())
moidx = get_frozen_mask(cc)
cell = cc._scf.cell
kpts = cc.kpts
nkpts = cc.nkpts
nocc = cc.nocc
nmo = cc.nmo
nvir = nmo - nocc
# if any(nocc != np.count_nonzero(cc._scf.mo_occ[k]>0)
# for k in range(nkpts)):
# raise NotImplementedError('Different occupancies found for different k-points')
if mo_coeff is None:
mo_coeff = cc.mo_coeff
dtype = mo_coeff[0].dtype
mo_coeff = self.mo_coeff = padded_mo_coeff(cc, mo_coeff)
# Re-make our fock MO matrix elements from density and fock AO
dm = cc._scf.make_rdm1(cc.mo_coeff, cc.mo_occ)
with lib.temporary_env(cc._scf, exxdiv=None):
# _scf.exxdiv affects eris.fock. HF exchange correction should be
# excluded from the Fock matrix.
fockao = cc._scf.get_hcore() + cc._scf.get_veff(cell, dm)
self.fock = np.asarray([reduce(np.dot, (mo.T.conj(), fockao[k], mo))
for k, mo in enumerate(mo_coeff)])
self.mo_energy = [self.fock[k].diagonal().real for k in range(nkpts)]
# Add HFX correction in the self.mo_energy to improve convergence in
# CCSD iteration. It is useful for the 2D systems since their occupied and
# the virtual orbital energies may overlap which may lead to numerical
# issue in the CCSD iterations.
# FIXME: Whether to add this correction for other exxdiv treatments?
# Without the correction, MP2 energy may be largely off the correct value.
madelung = tools.madelung(cell, kpts)
self.mo_energy = [_adjust_occ(mo_e, nocc, -madelung)
for k, mo_e in enumerate(self.mo_energy)]
# Get location of padded elements in occupied and virtual space.
nocc_per_kpt = get_nocc(cc, per_kpoint=True)
nonzero_padding = padding_k_idx(cc, kind="joint")
# Check direct and indirect gaps for possible issues with CCSD convergence.
mo_e = [self.mo_energy[kp][nonzero_padding[kp]] for kp in range(nkpts)]
mo_e = np.sort([y for x in mo_e for y in x]) # Sort de-nested array
gap = mo_e[np.sum(nocc_per_kpt)] - mo_e[np.sum(nocc_per_kpt)-1]
if gap < 1e-5:
logger.warn(cc, 'H**O-LUMO gap %s too small for KCCSD. '
'May cause issues in convergence.', gap)
mem_incore, mem_outcore, mem_basic = _mem_usage(nkpts, nocc, nvir)
mem_now = lib.current_memory()[0]
fao2mo = cc._scf.with_df.ao2mo
kconserv = cc.khelper.kconserv
khelper = cc.khelper
orbo = np.asarray(mo_coeff[:,:,:nocc], order='C')
orbv = np.asarray(mo_coeff[:,:,nocc:], order='C')
if (method == 'incore' and (mem_incore + mem_now < cc.max_memory)
or cell.incore_anyway):
log.info('using incore ERI storage')
self.oooo = np.empty((nkpts,nkpts,nkpts,nocc,nocc,nocc,nocc), dtype=dtype)
self.ooov = np.empty((nkpts,nkpts,nkpts,nocc,nocc,nocc,nvir), dtype=dtype)
self.oovv = np.empty((nkpts,nkpts,nkpts,nocc,nocc,nvir,nvir), dtype=dtype)
self.ovov = np.empty((nkpts,nkpts,nkpts,nocc,nvir,nocc,nvir), dtype=dtype)
self.voov = np.empty((nkpts,nkpts,nkpts,nvir,nocc,nocc,nvir), dtype=dtype)
self.vovv = np.empty((nkpts,nkpts,nkpts,nvir,nocc,nvir,nvir), dtype=dtype)
#self.vvvv = np.empty((nkpts,nkpts,nkpts,nvir,nvir,nvir,nvir), dtype=dtype)
self.vvvv = cc._scf.with_df.ao2mo_7d(orbv, factor=1./nkpts).transpose(0,2,1,3,5,4,6)
for (ikp,ikq,ikr) in khelper.symm_map.keys():
iks = kconserv[ikp,ikq,ikr]
eri_kpt = fao2mo((mo_coeff[ikp],mo_coeff[ikq],mo_coeff[ikr],mo_coeff[iks]),
(kpts[ikp],kpts[ikq],kpts[ikr],kpts[iks]), compact=False)
if dtype == np.float: eri_kpt = eri_kpt.real
eri_kpt = eri_kpt.reshape(nmo, nmo, nmo, nmo)
for (kp, kq, kr) in khelper.symm_map[(ikp, ikq, ikr)]:
eri_kpt_symm = khelper.transform_symm(eri_kpt, kp, kq, kr).transpose(0, 2, 1, 3)
self.oooo[kp, kr, kq] = eri_kpt_symm[:nocc, :nocc, :nocc, :nocc] / nkpts
self.ooov[kp, kr, kq] = eri_kpt_symm[:nocc, :nocc, :nocc, nocc:] / nkpts
self.oovv[kp, kr, kq] = eri_kpt_symm[:nocc, :nocc, nocc:, nocc:] / nkpts
self.ovov[kp, kr, kq] = eri_kpt_symm[:nocc, nocc:, :nocc, nocc:] / nkpts
self.voov[kp, kr, kq] = eri_kpt_symm[nocc:, :nocc, :nocc, nocc:] / nkpts
self.vovv[kp, kr, kq] = eri_kpt_symm[nocc:, :nocc, nocc:, nocc:] / nkpts
#self.vvvv[kp, kr, kq] = eri_kpt_symm[nocc:, nocc:, nocc:, nocc:] / nkpts
self.dtype = dtype
else:
log.info('using HDF5 ERI storage')
self.feri1 = lib.H5TmpFile()
self.oooo = self.feri1.create_dataset('oooo', (nkpts, nkpts, nkpts, nocc, nocc, nocc, nocc), dtype.char)
self.ooov = self.feri1.create_dataset('ooov', (nkpts, nkpts, nkpts, nocc, nocc, nocc, nvir), dtype.char)
self.oovv = self.feri1.create_dataset('oovv', (nkpts, nkpts, nkpts, nocc, nocc, nvir, nvir), dtype.char)
self.ovov = self.feri1.create_dataset('ovov', (nkpts, nkpts, nkpts, nocc, nvir, nocc, nvir), dtype.char)
self.voov = self.feri1.create_dataset('voov', (nkpts, nkpts, nkpts, nvir, nocc, nocc, nvir), dtype.char)
self.vovv = self.feri1.create_dataset('vovv', (nkpts, nkpts, nkpts, nvir, nocc, nvir, nvir), dtype.char)
vvvv_required = ((not cc.direct)
# cc._scf.with_df needs to be df.GDF only (not MDF)
or type(cc._scf.with_df) is not df.GDF
# direct-vvvv for pbc-2D is not supported so far
or cell.dimension == 2)
if vvvv_required:
self.vvvv = self.feri1.create_dataset('vvvv', (nkpts,nkpts,nkpts,nvir,nvir,nvir,nvir), dtype.char)
# <ij|pq> = (ip|jq)
cput1 = time.clock(), time.time()
for kp in range(nkpts):
for kq in range(nkpts):
for kr in range(nkpts):
ks = kconserv[kp, kq, kr]
orbo_p = mo_coeff[kp][:, :nocc]
orbo_r = mo_coeff[kr][:, :nocc]
buf_kpt = fao2mo((orbo_p, mo_coeff[kq], orbo_r, mo_coeff[ks]),
(kpts[kp], kpts[kq], kpts[kr], kpts[ks]), compact=False)
if mo_coeff[0].dtype == np.float: buf_kpt = buf_kpt.real
buf_kpt = buf_kpt.reshape(nocc, nmo, nocc, nmo).transpose(0, 2, 1, 3)
self.dtype = buf_kpt.dtype
self.oooo[kp, kr, kq, :, :, :, :] = buf_kpt[:, :, :nocc, :nocc] / nkpts
self.ooov[kp, kr, kq, :, :, :, :] = buf_kpt[:, :, :nocc, nocc:] / nkpts
self.oovv[kp, kr, kq, :, :, :, :] = buf_kpt[:, :, nocc:, nocc:] / nkpts
cput1 = log.timer_debug1('transforming oopq', *cput1)
# <ia|pq> = (ip|aq)
cput1 = time.clock(), time.time()
for kp in range(nkpts):
for kq in range(nkpts):
for kr in range(nkpts):
ks = kconserv[kp, kq, kr]
orbo_p = mo_coeff[kp][:, :nocc]
orbv_r = mo_coeff[kr][:, nocc:]
buf_kpt = fao2mo((orbo_p, mo_coeff[kq], orbv_r, mo_coeff[ks]),
(kpts[kp], kpts[kq], kpts[kr], kpts[ks]), compact=False)
if mo_coeff[0].dtype == np.float: buf_kpt = buf_kpt.real
buf_kpt = buf_kpt.reshape(nocc, nmo, nvir, nmo).transpose(0, 2, 1, 3)
self.ovov[kp, kr, kq, :, :, :, :] = buf_kpt[:, :, :nocc, nocc:] / nkpts
# TODO: compute vovv on the fly
self.vovv[kr, kp, ks, :, :, :, :] = buf_kpt[:, :, nocc:, nocc:].transpose(1, 0, 3, 2) / nkpts
self.voov[kr, kp, ks, :, :, :, :] = buf_kpt[:, :, nocc:, :nocc].transpose(1, 0, 3, 2) / nkpts
cput1 = log.timer_debug1('transforming ovpq', *cput1)
## Without k-point symmetry
# cput1 = time.clock(), time.time()
# for kp in range(nkpts):
# for kq in range(nkpts):
# for kr in range(nkpts):
# ks = kconserv[kp,kq,kr]
# orbv_p = mo_coeff[kp][:,nocc:]
# orbv_q = mo_coeff[kq][:,nocc:]
# orbv_r = mo_coeff[kr][:,nocc:]
# orbv_s = mo_coeff[ks][:,nocc:]
# for a in range(nvir):
# orbva_p = orbv_p[:,a].reshape(-1,1)
# buf_kpt = fao2mo((orbva_p,orbv_q,orbv_r,orbv_s),
# (kpts[kp],kpts[kq],kpts[kr],kpts[ks]), compact=False)
# if mo_coeff[0].dtype == np.float: buf_kpt = buf_kpt.real
# buf_kpt = buf_kpt.reshape((1,nvir,nvir,nvir)).transpose(0,2,1,3)
# self.vvvv[kp,kr,kq,a,:,:,:] = buf_kpt[:] / nkpts
# cput1 = log.timer_debug1('transforming vvvv', *cput1)
cput1 = time.clock(), time.time()
mem_now = lib.current_memory()[0]
if not vvvv_required:
_init_df_eris(cc, self)
elif nvir ** 4 * 16 / 1e6 + mem_now < cc.max_memory:
for (ikp, ikq, ikr) in khelper.symm_map.keys():
iks = kconserv[ikp, ikq, ikr]
orbv_p = mo_coeff[ikp][:, nocc:]
orbv_q = mo_coeff[ikq][:, nocc:]
orbv_r = mo_coeff[ikr][:, nocc:]
orbv_s = mo_coeff[iks][:, nocc:]
# unit cell is small enough to handle vvvv in-core
buf_kpt = fao2mo((orbv_p,orbv_q,orbv_r,orbv_s),
kpts[[ikp,ikq,ikr,iks]], compact=False)
if dtype == np.float: buf_kpt = buf_kpt.real
buf_kpt = buf_kpt.reshape((nvir, nvir, nvir, nvir))
for (kp, kq, kr) in khelper.symm_map[(ikp, ikq, ikr)]:
buf_kpt_symm = khelper.transform_symm(buf_kpt, kp, kq, kr).transpose(0, 2, 1, 3)
self.vvvv[kp, kr, kq] = buf_kpt_symm / nkpts
else:
raise MemoryError('Minimal memory requirements %s MB'
% (mem_now + nvir ** 4 / 1e6 * 16 * 2))
for (ikp, ikq, ikr) in khelper.symm_map.keys():
for a in range(nvir):
orbva_p = orbv_p[:, a].reshape(-1, 1)
buf_kpt = fao2mo((orbva_p, orbv_q, orbv_r, orbv_s),
(kpts[ikp], kpts[ikq], kpts[ikr], kpts[iks]), compact=False)
if mo_coeff[0].dtype == np.float: buf_kpt = buf_kpt.real
buf_kpt = buf_kpt.reshape((1, nvir, nvir, nvir)).transpose(0, 2, 1, 3)
self.vvvv[ikp, ikr, ikq, a, :, :, :] = buf_kpt[0, :, :, :] / nkpts
# Store symmetric permutations
self.vvvv[ikr, ikp, iks, :, a, :, :] = buf_kpt.transpose(1, 0, 3, 2)[:, 0, :, :] / nkpts
self.vvvv[ikq, iks, ikp, :, :, a, :] = buf_kpt.transpose(2, 3, 0, 1).conj()[:, :, 0, :] / nkpts
self.vvvv[iks, ikq, ikr, :, :, :, a] = buf_kpt.transpose(3, 2, 1, 0).conj()[:, :, :, 0] / nkpts
cput1 = log.timer_debug1('transforming vvvv', *cput1)
log.timer('CCSD integral transformation', *cput0)
def __init__(self, cc, mo_coeff=None):
from pyscf.pbc.cc.ccsd import _adjust_occ
import pyscf.pbc.tools.pbc as tools
if mo_coeff is None:
mo_coeff = cc.mo_coeff
cput0 = (time.clock(), time.time())
symlib = cc.symlib
log = Logger(cc.stdout, cc.verbose)
self.lib = lib
nocc, nmo, nkpts = cc.nocc, cc.nmo, cc.nkpts
nvir = nmo - nocc
cell, kpts = cc._scf.cell, cc.kpts
gvec = cell.reciprocal_vectors()
sym1 = ['+-', [kpts,]*2, None, gvec]
sym2 = ['+-+-', [kpts,]*4, None, gvec]
mo_coeff = self.mo_coeff = padded_mo_coeff(cc, mo_coeff)
nonzero_opadding, nonzero_vpadding = padding_k_idx(cc, kind="split")
madelung = tools.madelung(cell, kpts)
fock = None
if rank==0:
dm = cc._scf.make_rdm1(cc.mo_coeff, cc.mo_occ)
with pyscflib.temporary_env(cc._scf, exxdiv=None):
fockao = cc._scf.get_hcore() + cc._scf.get_veff(cell, dm)
fock = np.asarray([reduce(np.dot, (mo.T.conj(), fockao[k], mo))
for k, mo in enumerate(mo_coeff)])
fock = comm.bcast(fock, root=0)
self.dtype = dtype = np.result_type(*(mo_coeff, fock)).char
self.foo = zeros([nocc,nocc], dtype, sym1, symlib=symlib, verbose=cc.SYMVERBOSE)
self.fov = zeros([nocc,nvir], dtype, sym1, symlib=symlib, verbose=cc.SYMVERBOSE)
self.fvv = zeros([nvir,nvir], dtype, sym1, symlib=symlib, verbose=cc.SYMVERBOSE)
self.eia = zeros([nocc,nvir], np.float64, sym1, symlib=symlib, verbose=cc.SYMVERBOSE)
self._foo = zeros([nocc,nocc], dtype, sym1, symlib=symlib, verbose=cc.SYMVERBOSE)
self._fvv = zeros([nvir,nvir], dtype, sym1, symlib=symlib, verbose=cc.SYMVERBOSE)
foo = fock[:,:nocc,:nocc]
fov = fock[:,:nocc,nocc:]
fvv = fock[:,nocc:,nocc:]
mo_energy = [fock[k].diagonal().real for k in range(nkpts)]
mo_energy = [_adjust_occ(mo_e, nocc, -madelung)
for k, mo_e in enumerate(mo_energy)]
mo_e_o = [e[:nocc] for e in mo_energy]
mo_e_v = [e[nocc:] + cc.level_shift for e in mo_energy]
foo_ = np.asarray([np.diag(e) for e in mo_e_o])
fvv_ = np.asarray([np.diag(e) for e in mo_e_v])
eia = np.zeros([nkpts,nocc,nvir])
for ki in range(nkpts):
eia[ki] = _get_epq([0,nocc,ki,mo_e_o,nonzero_opadding],
[0,nvir,ki,mo_e_v,nonzero_vpadding],
fac=[1.0,-1.0])
if rank ==0:
self.foo.write(range(foo.size), foo.ravel())
self.fov.write(range(fov.size), fov.ravel())
self.fvv.write(range(fvv.size), fvv.ravel())
self.eia.write(range(eia.size), eia.ravel())
self._foo.write(range(foo_.size), foo_.ravel())
self._fvv.write(range(fvv_.size), fvv_.ravel())
else:
self.foo.write([],[])
self.fov.write([],[])
self.fvv.write([],[])
self.eia.write([],[])
self._foo.write([],[])
self._fvv.write([],[])
self.eijab = zeros([nocc,nocc,nvir,nvir], np.float64, sym2, symlib=symlib, verbose=cc.SYMVERBOSE)
kconserv = cc.khelper.kconserv
khelper = cc.khelper
idx_oovv = np.arange(nocc*nocc*nvir*nvir)
jobs = list(khelper.symm_map.keys())
tasks = static_partition(jobs)
ntasks = max(comm.allgather(len(tasks)))
nwrite = 0
for itask in tasks:
ikp, ikq, ikr = itask
pqr = np.asarray(khelper.symm_map[(ikp,ikq,ikr)])
nwrite += len(np.unique(pqr, axis=0))
nwrite_max = max(comm.allgather(nwrite))
write_count = 0
for itask in range(ntasks):
if itask >= len(tasks):
continue
ikp, ikq, ikr = tasks[itask]
iks = kconserv[ikp,ikq,ikr]
done = np.zeros([nkpts,nkpts,nkpts])
for (kp, kq, kr) in khelper.symm_map[(ikp, ikq, ikr)]:
if done[kp,kq,kr]: continue
ks = kconserv[kp,kq,kr]
eia = _get_epq([0,nocc,kp,mo_e_o,nonzero_opadding],
[0,nvir,kq,mo_e_v,nonzero_vpadding],
fac=[1.0,-1.0])
ejb = _get_epq([0,nocc,kr,mo_e_o,nonzero_opadding],
[0,nvir,ks,mo_e_v,nonzero_vpadding],
fac=[1.0,-1.0])
eijab = eia[:,None,:,None] + ejb[None,:,None,:]
off = kp * nkpts**2 + kr * nkpts + kq
self.eijab.write(off*idx_oovv.size+idx_oovv, eijab.ravel())
done[kp,kq,kr] = 1
write_count += 1
for i in range(nwrite_max-write_count):
self.eijab.write([], [])
if type(cc._scf.with_df) is df.FFTDF:
_make_fftdf_eris(cc, self)
else:
from cc_sym import mpigdf
if type(cc._scf.with_df) is mpigdf.GDF:
_make_df_eris(cc, self)
elif type(cc._scf.with_df) is df.GDF:
log.warn("GDF converted to an MPIGDF object")
cc._scf.with_df = mpigdf.from_serial(cc._scf.with_df)
_make_df_eris(cc, self)
else:
raise NotImplementedError("DF object not recognized")
log.timer("ao2mo transformation", *cput0)
def get_full_t3p2(mycc, t1, t2, eris):
'''Build the entire T3[2] array in memory.
'''
nkpts = mycc.nkpts
nocc = mycc.nocc
nmo = mycc.nmo
nvir = nmo - nocc
kconserv = mycc.khelper.kconserv
def get_wijkabc(ki, kj, kk, ka, kb, kc):
'''Build T3[2] for `ijkabc` at a given set of k-points'''
km = kconserv[kc, kk, kb]
kf = kconserv[kk, kc, kj]
ret = einsum('kjcf,ifab->ijkabc', t2[kk, kj, kc], eris.ovvv[ki, kf,
ka].conj())
ret = ret - einsum('jima,mkbc->ijkabc', eris.ooov[kj, ki, km].conj(),
t2[km, kk, kb])
return ret
#fock = eris.fock
#fov = fock[:, :nocc, nocc:]
#foo = numpy.array([fock[ikpt, :nocc, :nocc].diagonal() for ikpt in range(nkpts)])
#fvv = numpy.array([fock[ikpt, nocc:, nocc:].diagonal() for ikpt in range(nkpts)])
mo_energy_occ = numpy.array(
[eris.mo_energy[ki][:nocc] for ki in range(nkpts)])
mo_energy_vir = numpy.array(
[eris.mo_energy[ki][nocc:] for ki in range(nkpts)])
mo_e_o = mo_energy_occ
mo_e_v = mo_energy_vir
# Get location of padded elements in occupied and virtual space
nonzero_opadding, nonzero_vpadding = padding_k_idx(mycc, kind="split")
t3 = numpy.empty((nkpts, nkpts, nkpts, nkpts, nkpts, nocc, nocc, nocc,
nvir, nvir, nvir),
dtype=t2.dtype)
for ki, kj, kk, ka, kb in product(range(nkpts), repeat=5):
kc = kpts_helper.get_kconserv3(mycc._scf.cell, mycc.kpts,
[ki, kj, kk, ka, kb])
# Perform P(abc)
t3[ki, kj, kk, ka, kb] = get_wijkabc(ki, kj, kk, ka, kb, kc)
t3[ki, kj, kk, ka, kb] += get_wijkabc(ki, kj, kk, kb, kc,
ka).transpose(0, 1, 2, 5, 3, 4)
t3[ki, kj, kk, ka, kb] += get_wijkabc(ki, kj, kk, kc, ka,
kb).transpose(0, 1, 2, 4, 5, 3)
# Perform P(ijk)
t3 = (t3.transpose(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10) +
t3.transpose(1, 2, 0, 3, 4, 6, 7, 5, 8, 9, 10) +
t3.transpose(2, 0, 1, 3, 4, 7, 5, 6, 8, 9, 10))
for ki, kj, kk in product(range(nkpts), repeat=3):
eijk = _get_epqr([0, nocc, ki, mo_e_o, nonzero_opadding],
[0, nocc, kj, mo_e_o, nonzero_opadding],
[0, nocc, kk, mo_e_o, nonzero_opadding])
for ka, kb in product(range(nkpts), repeat=2):
kc = kpts_helper.get_kconserv3(mycc._scf.cell, mycc.kpts,
[ki, kj, kk, ka, kb])
eabc = _get_epqr([0, nvir, ka, mo_e_v, nonzero_vpadding],
[0, nvir, kb, mo_e_v, nonzero_vpadding],
[0, nvir, kc, mo_e_v, nonzero_vpadding],
fac=[-1., -1., -1.])
eijkabc = eijk[:, :, :, None, None, None] + eabc[None, None,
None, :, :, :]
t3[ki, kj, kk, ka, kb] /= eijkabc
return t3
def update_amps(cc, t1, t2, eris):
time0 = time.clock(), time.time()
log = logger.Logger(cc.stdout, cc.verbose)
nkpts, nocc, nvir = t1.shape
fock = eris.fock
mo_e_o = [e[:nocc] for e in eris.mo_energy]
mo_e_v = [e[nocc:] + cc.level_shift for e in eris.mo_energy]
# Get location of padded elements in occupied and virtual space
nonzero_opadding, nonzero_vpadding = padding_k_idx(cc, kind="split")
fov = fock[:, :nocc, nocc:].copy()
foo = fock[:, :nocc, :nocc].copy()
fvv = fock[:, nocc:, nocc:].copy()
# Get the momentum conservation array
# Note: chemist's notation for momentum conserving t2(ki,kj,ka,kb), even though
# integrals are in physics notation
kconserv = kpts_helper.get_kconserv(cc._scf.cell, cc.kpts)
tau = imdk.make_tau(cc, t2, t1, t1, kconserv)
Fvv = imdk.cc_Fvv(cc, t1, t2, eris, kconserv)
Foo = imdk.cc_Foo(cc, t1, t2, eris, kconserv)
Fov = imdk.cc_Fov(cc, t1, t2, eris, kconserv)
Woooo = imdk.cc_Woooo(cc, t1, t2, eris, kconserv)
Wvvvv = imdk.cc_Wvvvv(cc, t1, t2, eris, kconserv)
Wovvo = imdk.cc_Wovvo(cc, t1, t2, eris, kconserv)
# Move energy terms to the other side
for k in range(nkpts):
Foo[k][numpy.diag_indices(nocc)] -= mo_e_o[k]
Fvv[k][numpy.diag_indices(nvir)] -= mo_e_v[k]
eris_ovvo = numpy.zeros(shape=(nkpts, nkpts, nkpts, nocc, nvir, nvir,
nocc),
dtype=t2.dtype)
eris_oovo = numpy.zeros(shape=(nkpts, nkpts, nkpts, nocc, nocc, nvir,
nocc),
dtype=t2.dtype)
eris_vvvo = numpy.zeros(shape=(nkpts, nkpts, nkpts, nvir, nvir, nvir,
nocc),
dtype=t2.dtype)
for km, kb, ke in kpts_helper.loop_kkk(nkpts):
kj = kconserv[km, ke, kb]
# <mb||je> -> -<mb||ej>
eris_ovvo[km, kb, ke] = -eris.ovov[km, kb, kj].transpose(0, 1, 3, 2)
# <mn||je> -> -<mn||ej>
# let kb = kn as a dummy variable
eris_oovo[km, kb, ke] = -eris.ooov[km, kb, kj].transpose(0, 1, 3, 2)
# <ma||be> -> - <be||am>*
# let kj = ka as a dummy variable
kj = kconserv[km, ke, kb]
eris_vvvo[ke, kj,
kb] = -eris.ovvv[km, kb, ke].transpose(2, 3, 1, 0).conj()
# T1 equation
t1new = numpy.zeros(shape=t1.shape, dtype=t1.dtype)
for ka in range(nkpts):
ki = ka
t1new[ka] += numpy.array(fov[ka, :, :]).conj()
t1new[ka] += einsum('ie,ae->ia', t1[ka], Fvv[ka])
t1new[ka] += -einsum('ma,mi->ia', t1[ka], Foo[ka])
for km in range(nkpts):
t1new[ka] += einsum('imae,me->ia', t2[ka, km, ka], Fov[km])
t1new[ka] += -einsum('nf,naif->ia', t1[km], eris.ovov[km, ka, ki])
for kn in range(nkpts):
ke = kconserv[km, ki, kn]
t1new[ka] += -0.5 * einsum('imef,maef->ia', t2[ki, km, ke],
eris.ovvv[km, ka, ke])
t1new[ka] += -0.5 * einsum('mnae,nmei->ia', t2[km, kn, ka],
eris_oovo[kn, km, ke])
# T2 equation
t2new = numpy.array(eris.oovv).conj()
for ki, kj, ka in kpts_helper.loop_kkk(nkpts):
# Chemist's notation for momentum conserving t2(ki,kj,ka,kb)
kb = kconserv[ki, ka, kj]
Ftmp = Fvv[kb] - 0.5 * einsum('mb,me->be', t1[kb], Fov[kb])
tmp = einsum('ijae,be->ijab', t2[ki, kj, ka], Ftmp)
t2new[ki, kj, ka] += tmp
#t2new[ki,kj,kb] -= tmp.transpose(0,1,3,2)
Ftmp = Fvv[ka] - 0.5 * einsum('ma,me->ae', t1[ka], Fov[ka])
tmp = einsum('ijbe,ae->ijab', t2[ki, kj, kb], Ftmp)
t2new[ki, kj, ka] -= tmp
Ftmp = Foo[kj] + 0.5 * einsum('je,me->mj', t1[kj], Fov[kj])
tmp = einsum('imab,mj->ijab', t2[ki, kj, ka], Ftmp)
t2new[ki, kj, ka] -= tmp
#t2new[kj,ki,ka] += tmp.transpose(1,0,2,3)
Ftmp = Foo[ki] + 0.5 * einsum('ie,me->mi', t1[ki], Fov[ki])
tmp = einsum('jmab,mi->ijab', t2[kj, ki, ka], Ftmp)
t2new[ki, kj, ka] += tmp
for km in range(nkpts):
# Wminj
# - km - kn + ka + kb = 0
# => kn = ka - km + kb
kn = kconserv[ka, km, kb]
t2new[ki, kj, ka] += 0.5 * einsum(
'mnab,mnij->ijab', tau[km, kn, ka], Woooo[km, kn, ki])
ke = km
t2new[ki, kj, ka] += 0.5 * einsum(
'ijef,abef->ijab', tau[ki, kj, ke], Wvvvv[ka, kb, ke])
# Wmbej
# - km - kb + ke + kj = 0
# => ke = km - kj + kb
ke = kconserv[km, kj, kb]
tmp = einsum('imae,mbej->ijab', t2[ki, km, ka], Wovvo[km, kb, ke])
# - km - kb + ke + kj = 0
# => ke = km - kj + kb
#
# t[i,e] => ki = ke
# t[m,a] => km = ka
if km == ka and ke == ki:
tmp -= einsum('ie,ma,mbej->ijab', t1[ki], t1[km],
eris_ovvo[km, kb, ke])
t2new[ki, kj, ka] += tmp
t2new[ki, kj, kb] -= tmp.transpose(0, 1, 3, 2)
t2new[kj, ki, ka] -= tmp.transpose(1, 0, 2, 3)
t2new[kj, ki, kb] += tmp.transpose(1, 0, 3, 2)
ke = ki
tmp = einsum('ie,abej->ijab', t1[ki], eris_vvvo[ka, kb, ke])
t2new[ki, kj, ka] += tmp
# P(ij) term
ke = kj
tmp = einsum('je,abei->ijab', t1[kj], eris_vvvo[ka, kb, ke])
t2new[ki, kj, ka] -= tmp
km = ka
tmp = einsum('ma,mbij->ijab', t1[ka], eris.ovoo[km, kb, ki])
t2new[ki, kj, ka] -= tmp
# P(ab) term
km = kb
tmp = einsum('mb,maij->ijab', t1[kb], eris.ovoo[km, ka, ki])
t2new[ki, kj, ka] += tmp
for ki in range(nkpts):
ka = ki
# Remove zero/padded elements from denominator
eia = LARGE_DENOM * numpy.ones(
(nocc, nvir), dtype=eris.mo_energy[0].dtype)
n0_ovp_ia = numpy.ix_(nonzero_opadding[ki], nonzero_vpadding[ka])
eia[n0_ovp_ia] = (mo_e_o[ki][:, None] - mo_e_v[ka])[n0_ovp_ia]
t1new[ki] /= eia
kconserv = kpts_helper.get_kconserv(cc._scf.cell, cc.kpts)
for ki, kj, ka in kpts_helper.loop_kkk(nkpts):
kb = kconserv[ki, ka, kj]
# For LARGE_DENOM, see t1new update above
eia = LARGE_DENOM * numpy.ones(
(nocc, nvir), dtype=eris.mo_energy[0].dtype)
n0_ovp_ia = numpy.ix_(nonzero_opadding[ki], nonzero_vpadding[ka])
eia[n0_ovp_ia] = (mo_e_o[ki][:, None] - mo_e_v[ka])[n0_ovp_ia]
ejb = LARGE_DENOM * numpy.ones(
(nocc, nvir), dtype=eris.mo_energy[0].dtype)
n0_ovp_jb = numpy.ix_(nonzero_opadding[kj], nonzero_vpadding[kb])
ejb[n0_ovp_jb] = (mo_e_o[kj][:, None] - mo_e_v[kb])[n0_ovp_jb]
eijab = eia[:, None, :, None] + ejb[:, None, :]
t2new[ki, kj, ka] /= eijab
time0 = log.timer_debug1('update t1 t2', *time0)
return t1new, t2new
def get_t3p2_imds(mycc, t1, t2, eris=None, t3p2_ip_out=None, t3p2_ea_out=None):
"""For a description of arguments, see `get_t3p2_imds_slow` in
the corresponding `kintermediates.py`.
"""
from pyscf.pbc.cc.kccsd_t_rhf import _get_epqr
cpu1 = cpu0 = (logger.process_clock(), logger.perf_counter())
if eris is None:
eris = mycc.ao2mo()
fock = eris.fock
nkpts, nocc, nvir = t1.shape
cell = mycc._scf.cell
kpts = mycc.kpts
kconserv = mycc.khelper.kconserv
dtype = np.result_type(t1, t2)
fov = fock[:, :nocc, nocc:]
#foo = np.asarray([fock[ikpt, :nocc, :nocc].diagonal() for ikpt in range(nkpts)])
#fvv = np.asarray([fock[ikpt, nocc:, nocc:].diagonal() for ikpt in range(nkpts)])
mo_energy_occ = np.array(
[eris.mo_energy[ki][:nocc] for ki in range(nkpts)])
mo_energy_vir = np.array(
[eris.mo_energy[ki][nocc:] for ki in range(nkpts)])
mo_e_o = mo_energy_occ
mo_e_v = mo_energy_vir
ccsd_energy = mycc.energy(t1, t2, eris)
if t3p2_ip_out is None:
t3p2_ip_out = np.zeros((nkpts, nkpts, nkpts, nocc, nvir, nocc, nocc),
dtype=dtype)
Wmcik = t3p2_ip_out
if t3p2_ea_out is None:
t3p2_ea_out = np.zeros((nkpts, nkpts, nkpts, nvir, nvir, nvir, nocc),
dtype=dtype)
Wacek = t3p2_ea_out
# Create necessary temporary eris for fast read
from pyscf.pbc.cc.kccsd_t_rhf import create_t3_eris, get_data_slices
feri_tmp, t2T, eris_vvop, eris_vooo_C = create_t3_eris(
mycc, kconserv, [eris.vovv, eris.oovv, eris.ooov, t2])
#t1T = np.array([x.T for x in t1], dtype=np.complex, order='C')
#fvo = np.array([x.T for x in fov], dtype=np.complex, order='C')
cpu1 = logger.timer_debug1(mycc, 'CCSD(T) tmp eri creation', *cpu1)
def get_w(ki, kj, kk, ka, kb, kc, a0, a1, b0, b1, c0, c1):
'''Wijkabc intermediate as described in Scuseria paper before Pijkabc acts
Function copied for `kccsd_t_rhf.py`'''
km = kconserv[kc, kk, kb]
kf = kconserv[kk, kc, kj]
out = einsum('cfjk,abif->abcijk', t2T[kc, kf, kj, c0:c1, :, :, :],
eris_vvop[ka, kb, ki, a0:a1, b0:b1, :, nocc:])
out = out - einsum('cbmk,aijm->abcijk', t2T[kc, kb, km, c0:c1,
b0:b1, :, :],
eris_vooo_C[ka, ki, kj, a0:a1, :, :, :])
return out
def get_permuted_w(ki, kj, kk, ka, kb, kc, orb_indices):
'''Pijkabc operating on Wijkabc intermediate as described in Scuseria paper
Function copied for `kccsd_t_rhf.py`'''
a0, a1, b0, b1, c0, c1 = orb_indices
out = get_w(ki, kj, kk, ka, kb, kc, a0, a1, b0, b1, c0, c1)
out = out + get_w(kj, kk, ki, kb, kc, ka, b0, b1, c0, c1, a0,
a1).transpose(2, 0, 1, 5, 3, 4)
out = out + get_w(kk, ki, kj, kc, ka, kb, c0, c1, a0, a1, b0,
b1).transpose(1, 2, 0, 4, 5, 3)
out = out + get_w(ki, kk, kj, ka, kc, kb, a0, a1, c0, c1, b0,
b1).transpose(0, 2, 1, 3, 5, 4)
out = out + get_w(kk, kj, ki, kc, kb, ka, c0, c1, b0, b1, a0,
a1).transpose(2, 1, 0, 5, 4, 3)
out = out + get_w(kj, ki, kk, kb, ka, kc, b0, b1, a0, a1, c0,
c1).transpose(1, 0, 2, 4, 3, 5)
return out
def get_data(kpt_indices):
idx_args = get_data_slices(kpt_indices, task, kconserv)
vvop_indices, vooo_indices, t2T_vvop_indices, t2T_vooo_indices = idx_args
vvop_data = [eris_vvop[tuple(x)] for x in vvop_indices]
vooo_data = [eris_vooo_C[tuple(x)] for x in vooo_indices]
t2T_vvop_data = [t2T[tuple(x)] for x in t2T_vvop_indices]
t2T_vooo_data = [t2T[tuple(x)] for x in t2T_vooo_indices]
data = [vvop_data, vooo_data, t2T_vvop_data, t2T_vooo_data]
return data
def add_and_permute(kpt_indices, orb_indices, data):
'''Performs permutation and addition of t3 temporary arrays.'''
ki, kj, kk, ka, kb, kc = kpt_indices
a0, a1, b0, b1, c0, c1 = orb_indices
tmp_t3Tv_ijk = np.asarray(data[0], dtype=dtype, order='C')
tmp_t3Tv_jik = np.asarray(data[1], dtype=dtype, order='C')
tmp_t3Tv_kji = np.asarray(data[2], dtype=dtype, order='C')
#out_ijk = np.empty(data[0].shape, dtype=dtype, order='C')
#drv = _ccsd.libcc.MPICCadd_and_permute_t3T
#drv(ctypes.c_int(nocc), ctypes.c_int(nvir),
# ctypes.c_int(0),
# out_ijk.ctypes.data_as(ctypes.c_void_p),
# tmp_t3Tv_ijk.ctypes.data_as(ctypes.c_void_p),
# tmp_t3Tv_jik.ctypes.data_as(ctypes.c_void_p),
# tmp_t3Tv_kji.ctypes.data_as(ctypes.c_void_p),
# mo_offset.ctypes.data_as(ctypes.c_void_p),
# slices.ctypes.data_as(ctypes.c_void_p))
return (2. * tmp_t3Tv_ijk - tmp_t3Tv_jik.transpose(0, 1, 2, 4, 3, 5) -
tmp_t3Tv_kji.transpose(0, 1, 2, 5, 4, 3))
#return out_ijk
# Get location of padded elements in occupied and virtual space
nonzero_opadding, nonzero_vpadding = padding_k_idx(mycc, kind="split")
mem_now = lib.current_memory()[0]
max_memory = max(0, mycc.max_memory - mem_now)
blkmin = 4
# temporary t3 array is size: nkpts**3 * blksize**3 * nocc**3 * 16
vir_blksize = min(
nvir,
max(blkmin, int(
(max_memory * .9e6 / 16 / nocc**3 / nkpts**3)**(1. / 3))))
tasks = []
logger.debug(mycc, 'max_memory %d MB (%d MB in use)', max_memory, mem_now)
logger.debug(mycc, 'virtual blksize = %d (nvir = %d)', vir_blksize, nvir)
for a0, a1 in lib.prange(0, nvir, vir_blksize):
for b0, b1 in lib.prange(0, nvir, vir_blksize):
for c0, c1 in lib.prange(0, nvir, vir_blksize):
tasks.append((a0, a1, b0, b1, c0, c1))
eaa = []
for ka in range(nkpts):
eaa.append(mo_e_o[ka][:, None] - mo_e_v[ka][None, :])
pt1 = np.zeros((nkpts, nocc, nvir), dtype=dtype)
pt2 = np.zeros((nkpts, nkpts, nkpts, nocc, nocc, nvir, nvir), dtype=dtype)
for ka, kb in product(range(nkpts), repeat=2):
for task_id, task in enumerate(tasks):
cput2 = (logger.process_clock(), logger.perf_counter())
a0, a1, b0, b1, c0, c1 = task
my_permuted_w = np.zeros(
(nkpts, ) * 3 + (a1 - a0, b1 - b0, c1 - c0) + (nocc, ) * 3,
dtype=dtype)
for ki, kj, kk in product(range(nkpts), repeat=3):
# Find momentum conservation condition for triples
# amplitude t3ijkabc
kc = kpts_helper.get_kconserv3(cell, kpts,
[ki, kj, kk, ka, kb])
kpt_indices = [ki, kj, kk, ka, kb, kc]
#data = get_data(kpt_indices)
my_permuted_w[ki, kj,
kk] = get_permuted_w(ki, kj, kk, ka, kb, kc,
task)
for ki, kj, kk in product(range(nkpts), repeat=3):
# eigenvalue denominator: e(i) + e(j) + e(k)
eijk = _get_epqr([0, nocc, ki, mo_e_o, nonzero_opadding],
[0, nocc, kj, mo_e_o, nonzero_opadding],
[0, nocc, kk, mo_e_o, nonzero_opadding])
# Find momentum conservation condition for triples
# amplitude t3ijkabc
kc = kpts_helper.get_kconserv3(cell, kpts,
[ki, kj, kk, ka, kb])
eabc = _get_epqr([a0, a1, ka, mo_e_v, nonzero_vpadding],
[b0, b1, kb, mo_e_v, nonzero_vpadding],
[c0, c1, kc, mo_e_v, nonzero_vpadding],
fac=[-1., -1., -1.])
kpt_indices = [ki, kj, kk, ka, kb, kc]
eabcijk = (eijk[None, None, None, :, :, :] +
eabc[:, :, :, None, None, None])
tmp_t3Tv_ijk = my_permuted_w[ki, kj, kk]
tmp_t3Tv_jik = my_permuted_w[kj, ki, kk]
tmp_t3Tv_kji = my_permuted_w[kk, kj, ki]
Ptmp_t3Tv = add_and_permute(
kpt_indices, task,
(tmp_t3Tv_ijk, tmp_t3Tv_jik, tmp_t3Tv_kji))
Ptmp_t3Tv /= eabcijk
# Contribution to T1 amplitudes
if ki == ka and kc == kconserv[kj, kb, kk]:
eris_Soovv = (
2. * eris.oovv[kj, kk, kb, :, :, b0:b1, c0:c1] -
eris.oovv[kj, kk, kc, :, :, c0:c1, b0:b1].transpose(
0, 1, 3, 2))
pt1[ka, :, a0:a1] += 0.5 * einsum('abcijk,jkbc->ia',
Ptmp_t3Tv, eris_Soovv)
# Contribution to T2 amplitudes
if ki == ka and kc == kconserv[kj, kb, kk]:
tmp = einsum('abcijk,ia->jkbc', Ptmp_t3Tv,
0.5 * fov[ki, :, a0:a1])
_add_pt2(pt2, nkpts, kconserv, [kj, kk, kb],
[None, None, (b0, b1), (c0, c1)], tmp)
kd = kconserv[ka, ki, kb]
eris_vovv = eris.vovv[kd, ki, kb, :, :, b0:b1, a0:a1]
tmp = einsum('abcijk,diba->jkdc', Ptmp_t3Tv, eris_vovv)
_add_pt2(pt2, nkpts, kconserv, [kj, kk, kd],
[None, None, None, (c0, c1)], tmp)
km = kconserv[kc, kk, kb]
eris_ooov = eris.ooov[kj, ki, km, :, :, :, a0:a1]
tmp = einsum('abcijk,jima->mkbc', Ptmp_t3Tv, eris_ooov)
_add_pt2(pt2, nkpts, kconserv, [km, kk, kb],
[None, None, (b0, b1), (c0, c1)], -1. * tmp)
# Contribution to Wovoo array
km = kconserv[ka, ki, kc]
eris_oovv = eris.oovv[km, ki, kc, :, :, c0:c1, a0:a1]
tmp = einsum('abcijk,mica->mbkj', Ptmp_t3Tv, eris_oovv)
Wmcik[km, kb, kk, :, b0:b1, :, :] += tmp
# Contribution to Wvvoo array
ke = kconserv[ki, ka, kk]
eris_oovv = eris.oovv[ki, kk, ka, :, :, a0:a1, :]
tmp = einsum('abcijk,ikae->cbej', Ptmp_t3Tv, eris_oovv)
Wacek[kc, kb, ke, c0:c1, b0:b1, :, :] -= tmp
logger.timer_debug1(
mycc, 'EOM-CCSD T3[2] ka,kb,vir=(%d,%d,%d/%d) [total=%d]' %
(ka, kb, task_id, len(tasks), nkpts**5), *cput2)
for ki in range(nkpts):
ka = ki
eia = LARGE_DENOM * np.ones(
(nocc, nvir), dtype=eris.mo_energy[0].dtype)
n0_ovp_ia = np.ix_(nonzero_opadding[ki], nonzero_vpadding[ka])
eia[n0_ovp_ia] = (mo_e_o[ki][:, None] - mo_e_v[ka])[n0_ovp_ia]
pt1[ki] /= eia
for ki, ka in product(range(nkpts), repeat=2):
eia = LARGE_DENOM * np.ones(
(nocc, nvir), dtype=eris.mo_energy[0].dtype)
n0_ovp_ia = np.ix_(nonzero_opadding[ki], nonzero_vpadding[ka])
eia[n0_ovp_ia] = (mo_e_o[ki][:, None] - mo_e_v[ka])[n0_ovp_ia]
for kj in range(nkpts):
kb = kconserv[ki, ka, kj]
ejb = LARGE_DENOM * np.ones(
(nocc, nvir), dtype=eris.mo_energy[0].dtype)
n0_ovp_jb = np.ix_(nonzero_opadding[kj], nonzero_vpadding[kb])
ejb[n0_ovp_jb] = (mo_e_o[kj][:, None] - mo_e_v[kb])[n0_ovp_jb]
eijab = eia[:, None, :, None] + ejb[:, None, :]
pt2[ki, kj, ka] /= eijab
pt1 += t1
pt2 += t2
logger.timer(mycc, 'EOM-CCSD(T) imds', *cpu0)
delta_ccsd_energy = mycc.energy(pt1, pt2, eris) - ccsd_energy
logger.info(mycc, 'CCSD energy T3[2] correction : %16.12e',
delta_ccsd_energy)
return delta_ccsd_energy, pt1, pt2, Wmcik, Wacek
def kernel(mycc, eris, t1=None, t2=None, max_memory=2000, verbose=logger.INFO):
'''Returns the CCSD(T) for restricted closed-shell systems with k-points.
Note:
Returns real part of the CCSD(T) energy, raises warning if there is
a complex part.
Args:
mycc (:class:`RCCSD`): Coupled-cluster object storing results of
a coupled-cluster calculation.
eris (:class:`_ERIS`): Integral object holding the relevant electron-
repulsion integrals and Fock matrix elements
t1 (:obj:`ndarray`): t1 coupled-cluster amplitudes
t2 (:obj:`ndarray`): t2 coupled-cluster amplitudes
max_memory (float): Maximum memory used in calculation (NOT USED)
verbose (int, :class:`Logger`): verbosity of calculation
Returns:
energy_t (float): The real-part of the k-point CCSD(T) energy.
'''
assert isinstance(mycc, pyscf.pbc.cc.kccsd_rhf.RCCSD)
cpu1 = cpu0 = (logger.process_clock(), logger.perf_counter())
if isinstance(verbose, logger.Logger):
log = verbose
else:
log = logger.Logger(mycc.stdout, verbose)
if t1 is None: t1 = mycc.t1
if t2 is None: t2 = mycc.t2
if eris is None:
raise TypeError('Electron repulsion integrals, `eris`, must be passed in '
'to the CCSD(T) kernel or created in the cc object for '
'the k-point CCSD(T) to run!')
if t1 is None or t2 is None:
raise TypeError('Must pass in t1/t2 amplitudes to k-point CCSD(T)! (Maybe '
'need to run `.ccsd()` on the ccsd object?)')
cell = mycc._scf.cell
kpts = mycc.kpts
# The dtype of any local arrays that will be created
dtype = t1.dtype
nkpts, nocc, nvir = t1.shape
mo_energy_occ = [eris.mo_energy[ki][:nocc] for ki in range(nkpts)]
mo_energy_vir = [eris.mo_energy[ki][nocc:] for ki in range(nkpts)]
fov = eris.fock[:, :nocc, nocc:]
# Set up class for k-point conservation
kconserv = kpts_helper.get_kconserv(cell, kpts)
cpu1 = log.timer_debug1('CCSD(T) tmp eri creation', *cpu1)
def get_w(ki, kj, kk, ka, kb, kc, a0, a1, b0, b1, c0, c1, out=None):
'''Wijkabc intermediate as described in Scuseria paper before Pijkabc acts'''
km = kconserv[ki, ka, kj]
kf = kconserv[kk, kc, kj]
ret = einsum('kjcf,fiba->abcijk', t2[kk,kj,kc,:,:,c0:c1,:], eris.vovv[kf,ki,kb,:,:,b0:b1,a0:a1].conj())
ret = ret - einsum('mkbc,jima->abcijk', t2[km,kk,kb,:,:,b0:b1,c0:c1], eris.ooov[kj,ki,km,:,:,:,a0:a1].conj())
return ret
def get_permuted_w(ki, kj, kk, ka, kb, kc, orb_indices):
'''Pijkabc operating on Wijkabc intermediate as described in Scuseria paper'''
a0, a1, b0, b1, c0, c1 = orb_indices
out = get_w(ki, kj, kk, ka, kb, kc, a0, a1, b0, b1, c0, c1)
out = out + get_w(kj, kk, ki, kb, kc, ka, b0, b1, c0, c1, a0, a1).transpose(2,0,1,5,3,4)
out = out + get_w(kk, ki, kj, kc, ka, kb, c0, c1, a0, a1, b0, b1).transpose(1,2,0,4,5,3)
out = out + get_w(ki, kk, kj, ka, kc, kb, a0, a1, c0, c1, b0, b1).transpose(0,2,1,3,5,4)
out = out + get_w(kk, kj, ki, kc, kb, ka, c0, c1, b0, b1, a0, a1).transpose(2,1,0,5,4,3)
out = out + get_w(kj, ki, kk, kb, ka, kc, b0, b1, a0, a1, c0, c1).transpose(1,0,2,4,3,5)
return out
def get_rw(ki, kj, kk, ka, kb, kc, orb_indices):
'''R operating on Wijkabc intermediate as described in Scuseria paper'''
a0, a1, b0, b1, c0, c1 = orb_indices
ret = (4. * get_permuted_w(ki,kj,kk,ka,kb,kc,orb_indices) +
1. * get_permuted_w(kj,kk,ki,ka,kb,kc,orb_indices).transpose(0,1,2,5,3,4) +
1. * get_permuted_w(kk,ki,kj,ka,kb,kc,orb_indices).transpose(0,1,2,4,5,3) -
2. * get_permuted_w(ki,kk,kj,ka,kb,kc,orb_indices).transpose(0,1,2,3,5,4) -
2. * get_permuted_w(kk,kj,ki,ka,kb,kc,orb_indices).transpose(0,1,2,5,4,3) -
2. * get_permuted_w(kj,ki,kk,ka,kb,kc,orb_indices).transpose(0,1,2,4,3,5))
return ret
def get_v(ki, kj, kk, ka, kb, kc, a0, a1, b0, b1, c0, c1):
'''Vijkabc intermediate as described in Scuseria paper'''
out = np.zeros((a1-a0,b1-b0,c1-c0) + (nocc,)*3, dtype=dtype)
if kk == kc:
out = out + einsum('kc,ijab->abcijk', t1[kk,:,c0:c1], eris.oovv[ki,kj,ka,:,:,a0:a1,b0:b1].conj())
out = out + einsum('kc,ijab->abcijk', fov[kk,:,c0:c1], t2[ki,kj,ka,:,:,a0:a1,b0:b1])
return out
def get_permuted_v(ki, kj, kk, ka, kb, kc, orb_indices):
'''Pijkabc operating on Vijkabc intermediate as described in Scuseria paper'''
a0, a1, b0, b1, c0, c1 = orb_indices
ret = get_v(ki, kj, kk, ka, kb, kc, a0, a1, b0, b1, c0, c1)
ret = ret + get_v(kj, kk, ki, kb, kc, ka, b0, b1, c0, c1, a0, a1).transpose(2,0,1,5,3,4)
ret = ret + get_v(kk, ki, kj, kc, ka, kb, c0, c1, a0, a1, b0, b1).transpose(1,2,0,4,5,3)
ret = ret + get_v(ki, kk, kj, ka, kc, kb, a0, a1, c0, c1, b0, b1).transpose(0,2,1,3,5,4)
ret = ret + get_v(kk, kj, ki, kc, kb, ka, c0, c1, b0, b1, a0, a1).transpose(2,1,0,5,4,3)
ret = ret + get_v(kj, ki, kk, kb, ka, kc, b0, b1, a0, a1, c0, c1).transpose(1,0,2,4,3,5)
return ret
energy_t = 0.0
# Get location of padded elements in occupied and virtual space
nonzero_opadding, nonzero_vpadding = padding_k_idx(mycc, kind="split")
mem_now = lib.current_memory()[0]
max_memory = max(0, mycc.max_memory - mem_now)
blkmin = 4
# temporary t3 array is size: blksize**3 * nocc**3 * 16
vir_blksize = min(nvir, max(blkmin, int((max_memory*.9e6/16/nocc**3)**(1./3))))
tasks = []
log.debug('max_memory %d MB (%d MB in use)', max_memory, mem_now)
log.debug('virtual blksize = %d (nvir = %d)', nvir, vir_blksize)
for a0, a1 in lib.prange(0, nvir, vir_blksize):
for b0, b1 in lib.prange(0, nvir, vir_blksize):
for c0, c1 in lib.prange(0, nvir, vir_blksize):
tasks.append((a0,a1,b0,b1,c0,c1))
for ka in range(nkpts):
for kb in range(ka+1):
for ki, kj, kk in product(range(nkpts), repeat=3):
# eigenvalue denominator: e(i) + e(j) + e(k)
eijk = LARGE_DENOM * np.ones((nocc,)*3, dtype=mo_energy_occ[0].dtype)
n0_ovp_ijk = np.ix_(nonzero_opadding[ki], nonzero_opadding[kj], nonzero_opadding[kk])
eijk[n0_ovp_ijk] = lib.direct_sum('i,j,k->ijk', mo_energy_occ[ki],
mo_energy_occ[kj], mo_energy_occ[kk])[n0_ovp_ijk]
# Find momentum conservation condition for triples
# amplitude t3ijkabc
kc = kpts_helper.get_kconserv3(cell, kpts, [ki, kj, kk, ka, kb])
if not (ka >= kb and kb >= kc):
continue
if ka == kb and kb == kc:
symm_kpt = 1.
elif ka == kb or kb == kc:
symm_kpt = 3.
else:
symm_kpt = 6.
eabc = LARGE_DENOM * np.ones((nvir,)*3, dtype=mo_energy_occ[0].dtype)
n0_ovp_abc = np.ix_(nonzero_vpadding[ka], nonzero_vpadding[kb], nonzero_vpadding[kc])
eabc[n0_ovp_abc] = lib.direct_sum('i,j,k->ijk', mo_energy_vir[ka],
mo_energy_vir[kb], mo_energy_vir[kc])[n0_ovp_abc]
for task_id, task in enumerate(tasks):
eijkabc = (eijk[None,None,None,:,:,:] - eabc[a0:a1,b0:b1,c0:c1,None,None,None])
pwijk = (get_permuted_w(ki,kj,kk,ka,kb,kc,task) +
get_permuted_v(ki,kj,kk,ka,kb,kc,task) * 0.5)
rwijk = get_rw(ki,kj,kk,ka,kb,kc,task) / eijkabc
energy_t += symm_kpt * einsum('abcijk,abcijk', pwijk, rwijk.conj())
energy_t *= (1. / 3)
energy_t /= nkpts
if abs(energy_t.imag) > 1e-4:
log.warn('Non-zero imaginary part of CCSD(T) energy was found %s', energy_t.imag)
log.timer('CCSD(T)', *cpu0)
log.note('CCSD(T) correction per cell = %.15g', energy_t.real)
log.note('CCSD(T) correction per cell (imag) = %.15g', energy_t.imag)
return energy_t.real
def update_amps(cc, t1, t2, eris):
time0 = time.clock(), time.time()
log = logger.Logger(cc.stdout, cc.verbose)
nkpts, nocc, nvir = t1.shape
fock = eris.fock
mo_e_o = [e[:nocc] for e in eris.mo_energy]
mo_e_v = [e[nocc:] + cc.level_shift for e in eris.mo_energy]
# Get location of padded elements in occupied and virtual space
nonzero_opadding, nonzero_vpadding = padding_k_idx(cc, kind="split")
fov = fock[:, :nocc, nocc:].copy()
foo = fock[:, :nocc, :nocc].copy()
fvv = fock[:, nocc:, nocc:].copy()
# Get the momentum conservation array
# Note: chemist's notation for momentum conserving t2(ki,kj,ka,kb), even though
# integrals are in physics notation
kconserv = kpts_helper.get_kconserv(cc._scf.cell, cc.kpts)
tau = imdk.make_tau(cc, t2, t1, t1, kconserv)
Fvv = imdk.cc_Fvv(cc, t1, t2, eris, kconserv)
Foo = imdk.cc_Foo(cc, t1, t2, eris, kconserv)
Fov = imdk.cc_Fov(cc, t1, t2, eris, kconserv)
Woooo = imdk.cc_Woooo(cc, t1, t2, eris, kconserv)
Wvvvv = imdk.cc_Wvvvv(cc, t1, t2, eris, kconserv)
Wovvo = imdk.cc_Wovvo(cc, t1, t2, eris, kconserv)
# Move energy terms to the other side
for k in range(nkpts):
Foo[k][numpy.diag_indices(nocc)] -= mo_e_o[k]
Fvv[k][numpy.diag_indices(nvir)] -= mo_e_v[k]
eris_ovvo = numpy.zeros(shape=(nkpts, nkpts, nkpts, nocc, nvir, nvir, nocc), dtype=t2.dtype)
eris_oovo = numpy.zeros(shape=(nkpts, nkpts, nkpts, nocc, nocc, nvir, nocc), dtype=t2.dtype)
eris_vvvo = numpy.zeros(shape=(nkpts, nkpts, nkpts, nvir, nvir, nvir, nocc), dtype=t2.dtype)
for km, kb, ke in kpts_helper.loop_kkk(nkpts):
kj = kconserv[km, ke, kb]
# <mb||je> -> -<mb||ej>
eris_ovvo[km, kb, ke] = -eris.ovov[km, kb, kj].transpose(0, 1, 3, 2)
# <mn||je> -> -<mn||ej>
# let kb = kn as a dummy variable
eris_oovo[km, kb, ke] = -eris.ooov[km, kb, kj].transpose(0, 1, 3, 2)
# <ma||be> -> - <be||am>*
# let kj = ka as a dummy variable
kj = kconserv[km, ke, kb]
eris_vvvo[ke, kj, kb] = -eris.ovvv[km, kb, ke].transpose(2, 3, 1, 0).conj()
# T1 equation
t1new = numpy.zeros(shape=t1.shape, dtype=t1.dtype)
for ka in range(nkpts):
ki = ka
t1new[ka] += numpy.array(fov[ka, :, :]).conj()
t1new[ka] += einsum('ie,ae->ia', t1[ka], Fvv[ka])
t1new[ka] += -einsum('ma,mi->ia', t1[ka], Foo[ka])
for km in range(nkpts):
t1new[ka] += einsum('imae,me->ia', t2[ka, km, ka], Fov[km])
t1new[ka] += -einsum('nf,naif->ia', t1[km], eris.ovov[km, ka, ki])
for kn in range(nkpts):
ke = kconserv[km, ki, kn]
t1new[ka] += -0.5 * einsum('imef,maef->ia', t2[ki, km, ke], eris.ovvv[km, ka, ke])
t1new[ka] += -0.5 * einsum('mnae,nmei->ia', t2[km, kn, ka], eris_oovo[kn, km, ke])
# T2 equation
t2new = numpy.array(eris.oovv).conj()
for ki, kj, ka in kpts_helper.loop_kkk(nkpts):
# Chemist's notation for momentum conserving t2(ki,kj,ka,kb)
kb = kconserv[ki, ka, kj]
Ftmp = Fvv[kb] - 0.5 * einsum('mb,me->be', t1[kb], Fov[kb])
tmp = einsum('ijae,be->ijab', t2[ki, kj, ka], Ftmp)
t2new[ki, kj, ka] += tmp
#t2new[ki,kj,kb] -= tmp.transpose(0,1,3,2)
Ftmp = Fvv[ka] - 0.5 * einsum('ma,me->ae', t1[ka], Fov[ka])
tmp = einsum('ijbe,ae->ijab', t2[ki, kj, kb], Ftmp)
t2new[ki, kj, ka] -= tmp
Ftmp = Foo[kj] + 0.5 * einsum('je,me->mj', t1[kj], Fov[kj])
tmp = einsum('imab,mj->ijab', t2[ki, kj, ka], Ftmp)
t2new[ki, kj, ka] -= tmp
#t2new[kj,ki,ka] += tmp.transpose(1,0,2,3)
Ftmp = Foo[ki] + 0.5 * einsum('ie,me->mi', t1[ki], Fov[ki])
tmp = einsum('jmab,mi->ijab', t2[kj, ki, ka], Ftmp)
t2new[ki, kj, ka] += tmp
for km in range(nkpts):
# Wminj
# - km - kn + ka + kb = 0
# => kn = ka - km + kb
kn = kconserv[ka, km, kb]
t2new[ki, kj, ka] += 0.5 * einsum('mnab,mnij->ijab', tau[km, kn, ka], Woooo[km, kn, ki])
ke = km
t2new[ki, kj, ka] += 0.5 * einsum('ijef,abef->ijab', tau[ki, kj, ke], Wvvvv[ka, kb, ke])
# Wmbej
# - km - kb + ke + kj = 0
# => ke = km - kj + kb
ke = kconserv[km, kj, kb]
tmp = einsum('imae,mbej->ijab', t2[ki, km, ka], Wovvo[km, kb, ke])
# - km - kb + ke + kj = 0
# => ke = km - kj + kb
#
# t[i,e] => ki = ke
# t[m,a] => km = ka
if km == ka and ke == ki:
tmp -= einsum('ie,ma,mbej->ijab', t1[ki], t1[km], eris_ovvo[km, kb, ke])
t2new[ki, kj, ka] += tmp
t2new[ki, kj, kb] -= tmp.transpose(0, 1, 3, 2)
t2new[kj, ki, ka] -= tmp.transpose(1, 0, 2, 3)
t2new[kj, ki, kb] += tmp.transpose(1, 0, 3, 2)
ke = ki
tmp = einsum('ie,abej->ijab', t1[ki], eris_vvvo[ka, kb, ke])
t2new[ki, kj, ka] += tmp
# P(ij) term
ke = kj
tmp = einsum('je,abei->ijab', t1[kj], eris_vvvo[ka, kb, ke])
t2new[ki, kj, ka] -= tmp
km = ka
tmp = einsum('ma,mbij->ijab', t1[ka], eris.ovoo[km, kb, ki])
t2new[ki, kj, ka] -= tmp
# P(ab) term
km = kb
tmp = einsum('mb,maij->ijab', t1[kb], eris.ovoo[km, ka, ki])
t2new[ki, kj, ka] += tmp
for ki in range(nkpts):
ka = ki
# Remove zero/padded elements from denominator
eia = LARGE_DENOM * numpy.ones((nocc, nvir), dtype=eris.mo_energy[0].dtype)
n0_ovp_ia = numpy.ix_(nonzero_opadding[ki], nonzero_vpadding[ka])
eia[n0_ovp_ia] = (mo_e_o[ki][:,None] - mo_e_v[ka])[n0_ovp_ia]
t1new[ki] /= eia
kconserv = kpts_helper.get_kconserv(cc._scf.cell, cc.kpts)
for ki, kj, ka in kpts_helper.loop_kkk(nkpts):
kb = kconserv[ki, ka, kj]
# For LARGE_DENOM, see t1new update above
eia = LARGE_DENOM * numpy.ones((nocc, nvir), dtype=eris.mo_energy[0].dtype)
n0_ovp_ia = numpy.ix_(nonzero_opadding[ki], nonzero_vpadding[ka])
eia[n0_ovp_ia] = (mo_e_o[ki][:,None] - mo_e_v[ka])[n0_ovp_ia]
ejb = LARGE_DENOM * numpy.ones((nocc, nvir), dtype=eris.mo_energy[0].dtype)
n0_ovp_jb = numpy.ix_(nonzero_opadding[kj], nonzero_vpadding[kb])
ejb[n0_ovp_jb] = (mo_e_o[kj][:,None] - mo_e_v[kb])[n0_ovp_jb]
eijab = eia[:, None, :, None] + ejb[:, None, :]
t2new[ki, kj, ka] /= eijab
time0 = log.timer_debug1('update t1 t2', *time0)
return t1new, t2new
def _make_eris_incore(cc, mo_coeff=None):
from pyscf.pbc import tools
from pyscf.pbc.cc.ccsd import _adjust_occ
log = logger.Logger(cc.stdout, cc.verbose)
cput0 = (time.clock(), time.time())
eris = gccsd._PhysicistsERIs()
cell = cc._scf.cell
kpts = cc.kpts
nkpts = cc.nkpts
nocc = cc.nocc
nmo = cc.nmo
nvir = nmo - nocc
eris.nocc = nocc
#if any(nocc != numpy.count_nonzero(cc._scf.mo_occ[k] > 0) for k in range(nkpts)):
# raise NotImplementedError('Different occupancies found for different k-points')
if mo_coeff is None:
mo_coeff = cc.mo_coeff
nao = mo_coeff[0].shape[0]
dtype = mo_coeff[0].dtype
moidx = get_frozen_mask(cc)
nocc_per_kpt = numpy.asarray(get_nocc(cc, per_kpoint=True))
nmo_per_kpt = numpy.asarray(get_nmo(cc, per_kpoint=True))
padded_moidx = []
for k in range(nkpts):
kpt_nocc = nocc_per_kpt[k]
kpt_nvir = nmo_per_kpt[k] - kpt_nocc
kpt_padded_moidx = numpy.concatenate((numpy.ones(kpt_nocc, dtype=numpy.bool),
numpy.zeros(nmo - kpt_nocc - kpt_nvir, dtype=numpy.bool),
numpy.ones(kpt_nvir, dtype=numpy.bool)))
padded_moidx.append(kpt_padded_moidx)
eris.mo_coeff = []
eris.orbspin = []
# Generate the molecular orbital coefficients with the frozen orbitals masked.
# Each MO is tagged with orbspin, a list of 0's and 1's that give the overall
# spin of each MO.
#
# Here we will work with two index arrays; one is for our original (small) moidx
# array while the next is for our new (large) padded array.
for k in range(nkpts):
kpt_moidx = moidx[k]
kpt_padded_moidx = padded_moidx[k]
mo = numpy.zeros((nao, nmo), dtype=dtype)
mo[:, kpt_padded_moidx] = mo_coeff[k][:, kpt_moidx]
if getattr(mo_coeff[k], 'orbspin', None) is not None:
orbspin_dtype = mo_coeff[k].orbspin[kpt_moidx].dtype
orbspin = numpy.zeros(nmo, dtype=orbspin_dtype)
orbspin[kpt_padded_moidx] = mo_coeff[k].orbspin[kpt_moidx]
mo = lib.tag_array(mo, orbspin=orbspin)
eris.orbspin.append(orbspin)
# FIXME: What if the user freezes all up spin orbitals in
# an RHF calculation? The number of electrons will still be
# even.
else: # guess orbital spin - assumes an RHF calculation
assert (numpy.count_nonzero(kpt_moidx) % 2 == 0)
orbspin = numpy.zeros(mo.shape[1], dtype=int)
orbspin[1::2] = 1
mo = lib.tag_array(mo, orbspin=orbspin)
eris.orbspin.append(orbspin)
eris.mo_coeff.append(mo)
# Re-make our fock MO matrix elements from density and fock AO
dm = cc._scf.make_rdm1(cc.mo_coeff, cc.mo_occ)
with lib.temporary_env(cc._scf, exxdiv=None):
# _scf.exxdiv affects eris.fock. HF exchange correction should be
# excluded from the Fock matrix.
fockao = cc._scf.get_hcore() + cc._scf.get_veff(cell, dm)
eris.fock = numpy.asarray([reduce(numpy.dot, (mo.T.conj(), fockao[k], mo))
for k, mo in enumerate(eris.mo_coeff)])
eris.mo_energy = [eris.fock[k].diagonal().real for k in range(nkpts)]
# Add HFX correction in the eris.mo_energy to improve convergence in
# CCSD iteration. It is useful for the 2D systems since their occupied and
# the virtual orbital energies may overlap which may lead to numerical
# issue in the CCSD iterations.
# FIXME: Whether to add this correction for other exxdiv treatments?
# Without the correction, MP2 energy may be largely off the correct value.
madelung = tools.madelung(cell, kpts)
eris.mo_energy = [_adjust_occ(mo_e, nocc, -madelung)
for k, mo_e in enumerate(eris.mo_energy)]
# Get location of padded elements in occupied and virtual space.
nocc_per_kpt = get_nocc(cc, per_kpoint=True)
nonzero_padding = padding_k_idx(cc, kind="joint")
# Check direct and indirect gaps for possible issues with CCSD convergence.
mo_e = [eris.mo_energy[kp][nonzero_padding[kp]] for kp in range(nkpts)]
mo_e = numpy.sort([y for x in mo_e for y in x]) # Sort de-nested array
gap = mo_e[numpy.sum(nocc_per_kpt)] - mo_e[numpy.sum(nocc_per_kpt)-1]
if gap < 1e-5:
logger.warn(cc, 'H**O-LUMO gap %s too small for KCCSD. '
'May cause issues in convergence.', gap)
kconserv = kpts_helper.get_kconserv(cell, kpts)
if getattr(mo_coeff[0], 'orbspin', None) is None:
# The bottom nao//2 coefficients are down (up) spin while the top are up (down).
mo_a_coeff = [mo[:nao // 2] for mo in eris.mo_coeff]
mo_b_coeff = [mo[nao // 2:] for mo in eris.mo_coeff]
eri = numpy.empty((nkpts, nkpts, nkpts, nmo, nmo, nmo, nmo), dtype=numpy.complex128)
fao2mo = cc._scf.with_df.ao2mo
for kp, kq, kr in kpts_helper.loop_kkk(nkpts):
ks = kconserv[kp, kq, kr]
eri_kpt = fao2mo(
(mo_a_coeff[kp], mo_a_coeff[kq], mo_a_coeff[kr], mo_a_coeff[ks]), (kpts[kp], kpts[kq], kpts[kr], kpts[ks]),
compact=False)
eri_kpt += fao2mo(
(mo_b_coeff[kp], mo_b_coeff[kq], mo_b_coeff[kr], mo_b_coeff[ks]), (kpts[kp], kpts[kq], kpts[kr], kpts[ks]),
compact=False)
eri_kpt += fao2mo(
(mo_a_coeff[kp], mo_a_coeff[kq], mo_b_coeff[kr], mo_b_coeff[ks]), (kpts[kp], kpts[kq], kpts[kr], kpts[ks]),
compact=False)
eri_kpt += fao2mo(
(mo_b_coeff[kp], mo_b_coeff[kq], mo_a_coeff[kr], mo_a_coeff[ks]), (kpts[kp], kpts[kq], kpts[kr], kpts[ks]),
compact=False)
eri_kpt = eri_kpt.reshape(nmo, nmo, nmo, nmo)
eri[kp, kq, kr] = eri_kpt
else:
mo_a_coeff = [mo[:nao // 2] + mo[nao // 2:] for mo in eris.mo_coeff]
eri = numpy.empty((nkpts, nkpts, nkpts, nmo, nmo, nmo, nmo), dtype=numpy.complex128)
fao2mo = cc._scf.with_df.ao2mo
for kp, kq, kr in kpts_helper.loop_kkk(nkpts):
ks = kconserv[kp, kq, kr]
eri_kpt = fao2mo(
(mo_a_coeff[kp], mo_a_coeff[kq], mo_a_coeff[kr], mo_a_coeff[ks]), (kpts[kp], kpts[kq], kpts[kr], kpts[ks]),
compact=False)
eri_kpt[(eris.orbspin[kp][:, None] != eris.orbspin[kq]).ravel()] = 0
eri_kpt[:, (eris.orbspin[kr][:, None] != eris.orbspin[ks]).ravel()] = 0
eri_kpt = eri_kpt.reshape(nmo, nmo, nmo, nmo)
eri[kp, kq, kr] = eri_kpt
# Check some antisymmetrized properties of the integrals
if DEBUG:
check_antisymm_3412(cc, cc.kpts, eri)
# Antisymmetrizing (pq|rs)-(ps|rq), where the latter integral is equal to
# (rq|ps); done since we aren't tracking the kpoint of orbital 's'
eri = eri - eri.transpose(2, 1, 0, 5, 4, 3, 6)
# Chemist -> physics notation
eri = eri.transpose(0, 2, 1, 3, 5, 4, 6)
# Set the various integrals
eris.dtype = eri.dtype
eris.oooo = eri[:, :, :, :nocc, :nocc, :nocc, :nocc].copy() / nkpts
eris.ooov = eri[:, :, :, :nocc, :nocc, :nocc, nocc:].copy() / nkpts
eris.ovoo = eri[:, :, :, :nocc, nocc:, :nocc, :nocc].copy() / nkpts
eris.oovv = eri[:, :, :, :nocc, :nocc, nocc:, nocc:].copy() / nkpts
eris.ovov = eri[:, :, :, :nocc, nocc:, :nocc, nocc:].copy() / nkpts
eris.ovvv = eri[:, :, :, :nocc, nocc:, nocc:, nocc:].copy() / nkpts
eris.vvvv = eri[:, :, :, nocc:, nocc:, nocc:, nocc:].copy() / nkpts
log.timer('CCSD integral transformation', *cput0)
return eris
def _make_eris_incore(cc, mo_coeff=None):
from pyscf.pbc import tools
from pyscf.pbc.cc.ccsd import _adjust_occ
log = logger.Logger(cc.stdout, cc.verbose)
cput0 = (time.clock(), time.time())
eris = gccsd._PhysicistsERIs()
cell = cc._scf.cell
kpts = cc.kpts
nkpts = cc.nkpts
nocc = cc.nocc
nmo = cc.nmo
nvir = nmo - nocc
eris.nocc = nocc
#if any(nocc != numpy.count_nonzero(cc._scf.mo_occ[k] > 0) for k in range(nkpts)):
# raise NotImplementedError('Different occupancies found for different k-points')
if mo_coeff is None:
mo_coeff = cc.mo_coeff
nao = mo_coeff[0].shape[0]
dtype = mo_coeff[0].dtype
moidx = get_frozen_mask(cc)
nocc_per_kpt = numpy.asarray(get_nocc(cc, per_kpoint=True))
nmo_per_kpt = numpy.asarray(get_nmo(cc, per_kpoint=True))
padded_moidx = []
for k in range(nkpts):
kpt_nocc = nocc_per_kpt[k]
kpt_nvir = nmo_per_kpt[k] - kpt_nocc
kpt_padded_moidx = numpy.concatenate(
(numpy.ones(kpt_nocc, dtype=numpy.bool),
numpy.zeros(nmo - kpt_nocc - kpt_nvir, dtype=numpy.bool),
numpy.ones(kpt_nvir, dtype=numpy.bool)))
padded_moidx.append(kpt_padded_moidx)
eris.mo_coeff = []
eris.orbspin = []
# Generate the molecular orbital coefficients with the frozen orbitals masked.
# Each MO is tagged with orbspin, a list of 0's and 1's that give the overall
# spin of each MO.
#
# Here we will work with two index arrays; one is for our original (small) moidx
# array while the next is for our new (large) padded array.
for k in range(nkpts):
kpt_moidx = moidx[k]
kpt_padded_moidx = padded_moidx[k]
mo = numpy.zeros((nao, nmo), dtype=dtype)
mo[:, kpt_padded_moidx] = mo_coeff[k][:, kpt_moidx]
if getattr(mo_coeff[k], 'orbspin', None) is not None:
orbspin_dtype = mo_coeff[k].orbspin[kpt_moidx].dtype
orbspin = numpy.zeros(nmo, dtype=orbspin_dtype)
orbspin[kpt_padded_moidx] = mo_coeff[k].orbspin[kpt_moidx]
mo = lib.tag_array(mo, orbspin=orbspin)
eris.orbspin.append(orbspin)
# FIXME: What if the user freezes all up spin orbitals in
# an RHF calculation? The number of electrons will still be
# even.
else: # guess orbital spin - assumes an RHF calculation
assert (numpy.count_nonzero(kpt_moidx) % 2 == 0)
orbspin = numpy.zeros(mo.shape[1], dtype=int)
orbspin[1::2] = 1
mo = lib.tag_array(mo, orbspin=orbspin)
eris.orbspin.append(orbspin)
eris.mo_coeff.append(mo)
# Re-make our fock MO matrix elements from density and fock AO
dm = cc._scf.make_rdm1(cc.mo_coeff, cc.mo_occ)
with lib.temporary_env(cc._scf, exxdiv=None):
# _scf.exxdiv affects eris.fock. HF exchange correction should be
# excluded from the Fock matrix.
fockao = cc._scf.get_hcore() + cc._scf.get_veff(cell, dm)
eris.fock = numpy.asarray([
reduce(numpy.dot, (mo.T.conj(), fockao[k], mo))
for k, mo in enumerate(eris.mo_coeff)
])
eris.mo_energy = [eris.fock[k].diagonal().real for k in range(nkpts)]
# Add HFX correction in the eris.mo_energy to improve convergence in
# CCSD iteration. It is useful for the 2D systems since their occupied and
# the virtual orbital energies may overlap which may lead to numerical
# issue in the CCSD iterations.
# FIXME: Whether to add this correction for other exxdiv treatments?
# Without the correction, MP2 energy may be largely off the correct value.
madelung = tools.madelung(cell, kpts)
eris.mo_energy = [
_adjust_occ(mo_e, nocc, -madelung)
for k, mo_e in enumerate(eris.mo_energy)
]
# Get location of padded elements in occupied and virtual space.
nocc_per_kpt = get_nocc(cc, per_kpoint=True)
nonzero_padding = padding_k_idx(cc, kind="joint")
# Check direct and indirect gaps for possible issues with CCSD convergence.
mo_e = [eris.mo_energy[kp][nonzero_padding[kp]] for kp in range(nkpts)]
mo_e = numpy.sort([y for x in mo_e for y in x]) # Sort de-nested array
gap = mo_e[numpy.sum(nocc_per_kpt)] - mo_e[numpy.sum(nocc_per_kpt) - 1]
if gap < 1e-5:
logger.warn(
cc, 'H**O-LUMO gap %s too small for KCCSD. '
'May cause issues in convergence.', gap)
kconserv = kpts_helper.get_kconserv(cell, kpts)
if getattr(mo_coeff[0], 'orbspin', None) is None:
# The bottom nao//2 coefficients are down (up) spin while the top are up (down).
mo_a_coeff = [mo[:nao // 2] for mo in eris.mo_coeff]
mo_b_coeff = [mo[nao // 2:] for mo in eris.mo_coeff]
eri = numpy.empty((nkpts, nkpts, nkpts, nmo, nmo, nmo, nmo),
dtype=numpy.complex128)
fao2mo = cc._scf.with_df.ao2mo
for kp, kq, kr in kpts_helper.loop_kkk(nkpts):
ks = kconserv[kp, kq, kr]
eri_kpt = fao2mo((mo_a_coeff[kp], mo_a_coeff[kq], mo_a_coeff[kr],
mo_a_coeff[ks]),
(kpts[kp], kpts[kq], kpts[kr], kpts[ks]),
compact=False)
eri_kpt += fao2mo((mo_b_coeff[kp], mo_b_coeff[kq], mo_b_coeff[kr],
mo_b_coeff[ks]),
(kpts[kp], kpts[kq], kpts[kr], kpts[ks]),
compact=False)
eri_kpt += fao2mo((mo_a_coeff[kp], mo_a_coeff[kq], mo_b_coeff[kr],
mo_b_coeff[ks]),
(kpts[kp], kpts[kq], kpts[kr], kpts[ks]),
compact=False)
eri_kpt += fao2mo((mo_b_coeff[kp], mo_b_coeff[kq], mo_a_coeff[kr],
mo_a_coeff[ks]),
(kpts[kp], kpts[kq], kpts[kr], kpts[ks]),
compact=False)
eri_kpt = eri_kpt.reshape(nmo, nmo, nmo, nmo)
eri[kp, kq, kr] = eri_kpt
else:
mo_a_coeff = [mo[:nao // 2] + mo[nao // 2:] for mo in eris.mo_coeff]
eri = numpy.empty((nkpts, nkpts, nkpts, nmo, nmo, nmo, nmo),
dtype=numpy.complex128)
fao2mo = cc._scf.with_df.ao2mo
for kp, kq, kr in kpts_helper.loop_kkk(nkpts):
ks = kconserv[kp, kq, kr]
eri_kpt = fao2mo((mo_a_coeff[kp], mo_a_coeff[kq], mo_a_coeff[kr],
mo_a_coeff[ks]),
(kpts[kp], kpts[kq], kpts[kr], kpts[ks]),
compact=False)
eri_kpt[(eris.orbspin[kp][:, None] !=
eris.orbspin[kq]).ravel()] = 0
eri_kpt[:,
(eris.orbspin[kr][:,
None] != eris.orbspin[ks]).ravel()] = 0
eri_kpt = eri_kpt.reshape(nmo, nmo, nmo, nmo)
eri[kp, kq, kr] = eri_kpt
# Check some antisymmetrized properties of the integrals
if DEBUG:
check_antisymm_3412(cc, cc.kpts, eri)
# Antisymmetrizing (pq|rs)-(ps|rq), where the latter integral is equal to
# (rq|ps); done since we aren't tracking the kpoint of orbital 's'
eri = eri - eri.transpose(2, 1, 0, 5, 4, 3, 6)
# Chemist -> physics notation
eri = eri.transpose(0, 2, 1, 3, 5, 4, 6)
# Set the various integrals
eris.dtype = eri.dtype
eris.oooo = eri[:, :, :, :nocc, :nocc, :nocc, :nocc].copy() / nkpts
eris.ooov = eri[:, :, :, :nocc, :nocc, :nocc, nocc:].copy() / nkpts
eris.ovoo = eri[:, :, :, :nocc, nocc:, :nocc, :nocc].copy() / nkpts
eris.oovv = eri[:, :, :, :nocc, :nocc, nocc:, nocc:].copy() / nkpts
eris.ovov = eri[:, :, :, :nocc, nocc:, :nocc, nocc:].copy() / nkpts
eris.ovvv = eri[:, :, :, :nocc, nocc:, nocc:, nocc:].copy() / nkpts
eris.vvvv = eri[:, :, :, nocc:, nocc:, nocc:, nocc:].copy() / nkpts
log.timer('CCSD integral transformation', *cput0)
return eris
def assert_non_padded(cc, p, kp):
if p not in padding_k_idx(cc, kind="joint")[kp]:
raise PaddingError("The index p={:d} at k={:d} is padded".format(
p, kp))
def kernel(mycc, eris, t1=None, t2=None, max_memory=2000, verbose=logger.INFO):
'''Returns the CCSD(T) for restricted closed-shell systems with k-points.
Note:
Returns real part of the CCSD(T) energy, raises warning if there is
a complex part.
Args:
mycc (:class:`RCCSD`): Coupled-cluster object storing results of
a coupled-cluster calculation.
eris (:class:`_ERIS`): Integral object holding the relevant electron-
repulsion integrals and Fock matrix elements
t1 (:obj:`ndarray`): t1 coupled-cluster amplitudes
t2 (:obj:`ndarray`): t2 coupled-cluster amplitudes
max_memory (float): Maximum memory used in calculation (NOT USED)
verbose (int, :class:`Logger`): verbosity of calculation
Returns:
energy_t (float): The real-part of the k-point CCSD(T) energy.
'''
assert isinstance(mycc, pyscf.pbc.cc.kccsd_rhf.RCCSD)
cpu1 = cpu0 = (time.clock(), time.time())
if isinstance(verbose, logger.Logger):
log = verbose
else:
log = logger.Logger(mycc.stdout, verbose)
if t1 is None: t1 = mycc.t1
if t2 is None: t2 = mycc.t2
if eris is None:
raise TypeError(
'Electron repulsion integrals, `eris`, must be passed in '
'to the CCSD(T) kernel or created in the cc object for '
'the k-point CCSD(T) to run!')
if t1 is None or t2 is None:
raise TypeError(
'Must pass in t1/t2 amplitudes to k-point CCSD(T)! (Maybe '
'need to run `.ccsd()` on the ccsd object?)')
cell = mycc._scf.cell
kpts = mycc.kpts
# The dtype of any local arrays that will be created
dtype = t1.dtype
nkpts, nocc, nvir = t1.shape
mo_energy_occ = [eris.mo_energy[ki][:nocc] for ki in range(nkpts)]
mo_energy_vir = [eris.mo_energy[ki][nocc:] for ki in range(nkpts)]
mo_energy = np.asarray([eris.mo_energy[ki] for ki in range(nkpts)],
dtype=np.float,
order='C')
fov = eris.fock[:, :nocc, nocc:]
mo_e = mo_energy
mo_e_o = mo_energy_occ
mo_e_v = mo_energy_vir
# Set up class for k-point conservation
kconserv = kpts_helper.get_kconserv(cell, kpts)
# Create necessary temporary eris for fast read
feri_tmp, t2T, eris_vvop, eris_vooo_C = create_t3_eris(
mycc, kconserv, [eris.vovv, eris.oovv, eris.ooov, t2])
t1T = np.array([x.T for x in t1], dtype=np.complex, order='C')
fvo = np.array([x.T for x in fov], dtype=np.complex, order='C')
cpu1 = log.timer_debug1('CCSD(T) tmp eri creation', *cpu1)
#def get_w_old(ki, kj, kk, ka, kb, kc, a0, a1, b0, b1, c0, c1, out=None):
# '''Wijkabc intermediate as described in Scuseria paper before Pijkabc acts'''
# km = kconserv[kc, kk, kb]
# kf = kconserv[kk, kc, kj]
# ret = einsum('kjcf,fiba->abcijk', t2[kk,kj,kc,:,:,c0:c1,:], eris.vovv[kf,ki,kb,:,:,b0:b1,a0:a1].conj())
# ret = ret - einsum('mkbc,jima->abcijk', t2[km,kk,kb,:,:,b0:b1,c0:c1], eris.ooov[kj,ki,km,:,:,:,a0:a1].conj())
# return ret
def get_w(ki, kj, kk, ka, kb, kc, a0, a1, b0, b1, c0, c1):
'''Wijkabc intermediate as described in Scuseria paper before Pijkabc acts
Uses tranposed eris for fast data access.'''
km = kconserv[kc, kk, kb]
kf = kconserv[kk, kc, kj]
out = einsum('cfjk,abif->abcijk', t2T[kc, kf, kj, c0:c1, :, :, :],
eris_vvop[ka, kb, ki, a0:a1, b0:b1, :, nocc:])
out = out - einsum('cbmk,aijm->abcijk', t2T[kc, kb, km, c0:c1,
b0:b1, :, :],
eris_vooo_C[ka, ki, kj, a0:a1, :, :, :])
return out
def get_permuted_w(ki, kj, kk, ka, kb, kc, orb_indices):
'''Pijkabc operating on Wijkabc intermediate as described in Scuseria paper'''
a0, a1, b0, b1, c0, c1 = orb_indices
out = get_w(ki, kj, kk, ka, kb, kc, a0, a1, b0, b1, c0, c1)
out = out + get_w(kj, kk, ki, kb, kc, ka, b0, b1, c0, c1, a0,
a1).transpose(2, 0, 1, 5, 3, 4)
out = out + get_w(kk, ki, kj, kc, ka, kb, c0, c1, a0, a1, b0,
b1).transpose(1, 2, 0, 4, 5, 3)
out = out + get_w(ki, kk, kj, ka, kc, kb, a0, a1, c0, c1, b0,
b1).transpose(0, 2, 1, 3, 5, 4)
out = out + get_w(kk, kj, ki, kc, kb, ka, c0, c1, b0, b1, a0,
a1).transpose(2, 1, 0, 5, 4, 3)
out = out + get_w(kj, ki, kk, kb, ka, kc, b0, b1, a0, a1, c0,
c1).transpose(1, 0, 2, 4, 3, 5)
return out
def get_rw(ki, kj, kk, ka, kb, kc, orb_indices):
'''R operating on Wijkabc intermediate as described in Scuseria paper'''
a0, a1, b0, b1, c0, c1 = orb_indices
ret = (4. * get_permuted_w(ki, kj, kk, ka, kb, kc, orb_indices) +
1. * get_permuted_w(kj, kk, ki, ka, kb, kc,
orb_indices).transpose(0, 1, 2, 5, 3, 4) +
1. * get_permuted_w(kk, ki, kj, ka, kb, kc,
orb_indices).transpose(0, 1, 2, 4, 5, 3) -
2. * get_permuted_w(ki, kk, kj, ka, kb, kc,
orb_indices).transpose(0, 1, 2, 3, 5, 4) -
2. * get_permuted_w(kk, kj, ki, ka, kb, kc,
orb_indices).transpose(0, 1, 2, 5, 4, 3) -
2. * get_permuted_w(kj, ki, kk, ka, kb, kc,
orb_indices).transpose(0, 1, 2, 4, 3, 5))
return ret
#def get_v_old(ki, kj, kk, ka, kb, kc, a0, a1, b0, b1, c0, c1):
# '''Vijkabc intermediate as described in Scuseria paper'''
# km = kconserv[ki,ka,kj]
# kf = kconserv[ki,ka,kj]
# out = np.zeros((a1-a0,b1-b0,c1-c0) + (nocc,)*3, dtype=dtype)
# if kk == kc:
# out = out + einsum('kc,ijab->abcijk', 0.5*t1[kk,:,c0:c1], eris.oovv[ki,kj,ka,:,:,a0:a1,b0:b1].conj())
# out = out + einsum('kc,ijab->abcijk', 0.5*fov[kk,:,c0:c1], t2[ki,kj,ka,:,:,a0:a1,b0:b1])
# return out
def get_v(ki, kj, kk, ka, kb, kc, a0, a1, b0, b1, c0, c1):
'''Vijkabc intermediate as described in Scuseria paper'''
km = kconserv[ki, ka, kj]
kf = kconserv[ki, ka, kj]
out = np.zeros((a1 - a0, b1 - b0, c1 - c0) + (nocc, ) * 3, dtype=dtype)
if kk == kc:
out = out + einsum('ck,baji->abcijk', 0.5 * t1T[kk, c0:c1, :],
eris_vvop[kb, ka, kj, b0:b1, a0:a1, :, :nocc])
# We see this is the same t2T term needed for the `w` contraction:
# einsum('cbmk,aijm->abcijk', t2T[kc,kb,km,c0:c1,b0:b1], eris_vooo_C[ka,ki,kj,a0:a1])
#
# For the kpoint indices [kk,ki,kj,kc,ka,kb] we have that we need
# t2T[kb,ka,km], where km = kconserv[kb,kj,ka]
# The remaining k-point not used in t2T, i.e. kc, has the condition kc == kk in the case of
# get_v. So, we have from 3-particle conservation
# (kk-kc) + ki + kj - ka - kb = 0,
# i.e. ki = km.
out = out + einsum('ck,baij->abcijk', 0.5 * fvo[kk, c0:c1, :],
t2T[kb, ka, ki, b0:b1, a0:a1, :, :])
return out
def get_permuted_v(ki, kj, kk, ka, kb, kc, orb_indices):
'''Pijkabc operating on Vijkabc intermediate as described in Scuseria paper'''
a0, a1, b0, b1, c0, c1 = orb_indices
tmp = np.zeros((a1 - a0, b1 - b0, c1 - c0) + (nocc, ) * 3, dtype=dtype)
ret = get_v(ki, kj, kk, ka, kb, kc, a0, a1, b0, b1, c0, c1)
ret = ret + get_v(kj, kk, ki, kb, kc, ka, b0, b1, c0, c1, a0,
a1).transpose(2, 0, 1, 5, 3, 4)
ret = ret + get_v(kk, ki, kj, kc, ka, kb, c0, c1, a0, a1, b0,
b1).transpose(1, 2, 0, 4, 5, 3)
ret = ret + get_v(ki, kk, kj, ka, kc, kb, a0, a1, c0, c1, b0,
b1).transpose(0, 2, 1, 3, 5, 4)
ret = ret + get_v(kk, kj, ki, kc, kb, ka, c0, c1, b0, b1, a0,
a1).transpose(2, 1, 0, 5, 4, 3)
ret = ret + get_v(kj, ki, kk, kb, ka, kc, b0, b1, a0, a1, c0,
c1).transpose(1, 0, 2, 4, 3, 5)
return ret
def contract_t3Tv(kpt_indices, orb_indices, data):
'''Calculate t3T(ransposed) array using C driver.'''
ki, kj, kk, ka, kb, kc = kpt_indices
a0, a1, b0, b1, c0, c1 = orb_indices
slices = np.array([a0, a1, b0, b1, c0, c1], dtype=np.int32)
mo_offset = np.array([ki, kj, kk, ka, kb, kc], dtype=np.int32)
vvop_ab = np.asarray(data[0][0], dtype=np.complex, order='C')
vvop_ac = np.asarray(data[0][1], dtype=np.complex, order='C')
vvop_ba = np.asarray(data[0][2], dtype=np.complex, order='C')
vvop_bc = np.asarray(data[0][3], dtype=np.complex, order='C')
vvop_ca = np.asarray(data[0][4], dtype=np.complex, order='C')
vvop_cb = np.asarray(data[0][5], dtype=np.complex, order='C')
vooo_aj = np.asarray(data[1][0], dtype=np.complex, order='C')
vooo_ak = np.asarray(data[1][1], dtype=np.complex, order='C')
vooo_bi = np.asarray(data[1][2], dtype=np.complex, order='C')
vooo_bk = np.asarray(data[1][3], dtype=np.complex, order='C')
vooo_ci = np.asarray(data[1][4], dtype=np.complex, order='C')
vooo_cj = np.asarray(data[1][5], dtype=np.complex, order='C')
t2T_cj = np.asarray(data[2][0], dtype=np.complex, order='C')
t2T_bk = np.asarray(data[2][1], dtype=np.complex, order='C')
t2T_ci = np.asarray(data[2][2], dtype=np.complex, order='C')
t2T_ak = np.asarray(data[2][3], dtype=np.complex, order='C')
t2T_bi = np.asarray(data[2][4], dtype=np.complex, order='C')
t2T_aj = np.asarray(data[2][5], dtype=np.complex, order='C')
t2T_cb = np.asarray(data[3][0], dtype=np.complex, order='C')
t2T_bc = np.asarray(data[3][1], dtype=np.complex, order='C')
t2T_ca = np.asarray(data[3][2], dtype=np.complex, order='C')
t2T_ac = np.asarray(data[3][3], dtype=np.complex, order='C')
t2T_ba = np.asarray(data[3][4], dtype=np.complex, order='C')
t2T_ab = np.asarray(data[3][5], dtype=np.complex, order='C')
data = [
vvop_ab, vvop_ac, vvop_ba, vvop_bc, vvop_ca, vvop_cb, vooo_aj,
vooo_ak, vooo_bi, vooo_bk, vooo_ci, vooo_cj, t2T_cj, t2T_cb,
t2T_bk, t2T_bc, t2T_ci, t2T_ca, t2T_ak, t2T_ac, t2T_bi, t2T_ba,
t2T_aj, t2T_ab
]
data_ptrs = [x.ctypes.data_as(ctypes.c_void_p) for x in data]
data_ptrs = (ctypes.c_void_p * 24)(*data_ptrs)
a0, a1, b0, b1, c0, c1 = task
t3Tw = np.empty((a1 - a0, b1 - b0, c1 - c0) + (nocc, ) * 3,
dtype=np.complex,
order='C')
t3Tv = np.empty((a1 - a0, b1 - b0, c1 - c0) + (nocc, ) * 3,
dtype=np.complex,
order='C')
drv = _ccsd.libcc.CCsd_zcontract_t3T
drv(t3Tw.ctypes.data_as(ctypes.c_void_p),
t3Tv.ctypes.data_as(ctypes.c_void_p),
mo_e.ctypes.data_as(ctypes.c_void_p),
t1T.ctypes.data_as(ctypes.c_void_p),
fvo.ctypes.data_as(ctypes.c_void_p), ctypes.c_int(nocc),
ctypes.c_int(nvir), ctypes.c_int(nkpts),
mo_offset.ctypes.data_as(ctypes.c_void_p),
slices.ctypes.data_as(ctypes.c_void_p), data_ptrs)
return t3Tw, t3Tv
def get_data(kpt_indices):
idx_args = get_data_slices(kpt_indices, task, kconserv)
vvop_indices, vooo_indices, t2T_vvop_indices, t2T_vooo_indices = idx_args
vvop_data = [eris_vvop[tuple(x)] for x in vvop_indices]
vooo_data = [eris_vooo_C[tuple(x)] for x in vooo_indices]
t2T_vvop_data = [t2T[tuple(x)] for x in t2T_vvop_indices]
t2T_vooo_data = [t2T[tuple(x)] for x in t2T_vooo_indices]
data = [vvop_data, vooo_data, t2T_vvop_data, t2T_vooo_data]
return data
energy_t = 0.0
# Get location of padded elements in occupied and virtual space
nonzero_opadding, nonzero_vpadding = padding_k_idx(mycc, kind="split")
mem_now = lib.current_memory()[0]
max_memory = max(0, mycc.max_memory - mem_now)
blkmin = 4
# temporary t3 array is size: 2 * nkpts**3 * blksize**3 * nocc**3 * 16
vir_blksize = min(
nvir,
max(blkmin,
int((max_memory * .9e6 / 16 / nocc**3 / nkpts**3 / 2)**(1. / 3))))
tasks = []
log.debug('max_memory %d MB (%d MB in use)', max_memory, mem_now)
log.debug('virtual blksize = %d (nvir = %d)', nvir, vir_blksize)
for a0, a1 in lib.prange(0, nvir, vir_blksize):
for b0, b1 in lib.prange(0, nvir, vir_blksize):
for c0, c1 in lib.prange(0, nvir, vir_blksize):
tasks.append((a0, a1, b0, b1, c0, c1))
for ka in range(nkpts):
for kb in range(ka + 1):
for task_id, task in enumerate(tasks):
a0, a1, b0, b1, c0, c1 = task
my_permuted_w = np.zeros(
(nkpts, ) * 3 + (a1 - a0, b1 - b0, c1 - c0) + (nocc, ) * 3,
dtype=dtype)
my_permuted_v = np.zeros(
(nkpts, ) * 3 + (a1 - a0, b1 - b0, c1 - c0) + (nocc, ) * 3,
dtype=dtype)
for ki, kj, kk in product(range(nkpts), repeat=3):
# Find momentum conservation condition for triples
# amplitude t3ijkabc
kc = kpts_helper.get_kconserv3(cell, kpts,
[ki, kj, kk, ka, kb])
if not (ka >= kb and kb >= kc):
continue
kpt_indices = [ki, kj, kk, ka, kb, kc]
data = get_data(kpt_indices)
t3Tw, t3Tv = contract_t3Tv(kpt_indices, task, data)
my_permuted_w[ki, kj, kk] = t3Tw
my_permuted_v[ki, kj, kk] = t3Tv
#my_permuted_w[ki,kj,kk] = get_permuted_w(ki,kj,kk,ka,kb,kc,task)
#my_permuted_v[ki,kj,kk] = get_permuted_v(ki,kj,kk,ka,kb,kc,task)
for ki, kj, kk in product(range(nkpts), repeat=3):
# eigenvalue denominator: e(i) + e(j) + e(k)
eijk = _get_epqr([0, nocc, ki, mo_e_o, nonzero_opadding],
[0, nocc, kj, mo_e_o, nonzero_opadding],
[0, nocc, kk, mo_e_o, nonzero_opadding])
# Find momentum conservation condition for triples
# amplitude t3ijkabc
kc = kpts_helper.get_kconserv3(cell, kpts,
[ki, kj, kk, ka, kb])
if not (ka >= kb and kb >= kc):
continue
if ka == kb and kb == kc:
symm_kpt = 1.
elif ka == kb or kb == kc:
symm_kpt = 3.
else:
symm_kpt = 6.
eabc = _get_epqr([a0, a1, ka, mo_e_v, nonzero_vpadding],
[b0, b1, kb, mo_e_v, nonzero_vpadding],
[c0, c1, kc, mo_e_v, nonzero_vpadding],
fac=[-1., -1., -1.])
eijkabc = (eijk[None, None, None, :, :, :] +
eabc[:, :, :, None, None, None])
pwijk = my_permuted_w[ki, kj, kk] + my_permuted_v[ki, kj,
kk]
rwijk = (
4. * my_permuted_w[ki, kj, kk] + 1. *
my_permuted_w[kj, kk, ki].transpose(0, 1, 2, 5, 3, 4) +
1. *
my_permuted_w[kk, ki, kj].transpose(0, 1, 2, 4, 5, 3) -
2. *
my_permuted_w[ki, kk, kj].transpose(0, 1, 2, 3, 5, 4) -
2. *
my_permuted_w[kk, kj, ki].transpose(0, 1, 2, 5, 4, 3) -
2. *
my_permuted_w[kj, ki, kk].transpose(0, 1, 2, 4, 3, 5))
rwijk = rwijk / eijkabc
energy_t += symm_kpt * einsum('abcijk,abcijk', rwijk,
pwijk.conj())
energy_t *= (1. / 3)
energy_t /= nkpts
if abs(energy_t.imag) > 1e-4:
log.warn('Non-zero imaginary part of CCSD(T) energy was found %s',
energy_t.imag)
log.timer('CCSD(T)', *cpu0)
log.note('CCSD(T) correction per cell = %.15g', energy_t.real)
log.note('CCSD(T) correction per cell (imag) = %.15g', energy_t.imag)
return energy_t.real
def __init__(self, cc, mo_coeff=None):
from pyscf.pbc.cc.ccsd import _adjust_occ
import pyscf.pbc.tools.pbc as tools
if mo_coeff is None:
mo_coeff = cc.mo_coeff
cput0 = (time.clock(), time.time())
log = Logger(cc.stdout, cc.verbose)
self.lib = lib
nocc, nmo, nkpts = cc.nocc, cc.nmo, cc.nkpts
nvir = nmo - nocc
cell, kpts = cc._scf.cell, cc.kpts
gvec = cell.reciprocal_vectors()
sym1 = ['+-', [
kpts,
] * 2, None, gvec]
sym2 = ['+-+-', [
kpts,
] * 4, None, gvec]
mo_coeff = self.mo_coeff = padded_mo_coeff(cc, mo_coeff)
nonzero_opadding, nonzero_vpadding = padding_k_idx(cc, kind="split")
madelung = tools.madelung(cell, kpts)
dm = cc._scf.make_rdm1(cc.mo_coeff, cc.mo_occ)
with pyscflib.temporary_env(cc._scf, exxdiv=None):
fockao = cc._scf.get_hcore() + cc._scf.get_veff(cell, dm)
fock = np.asarray([
reduce(np.dot, (mo.T.conj(), fockao[k], mo))
for k, mo in enumerate(mo_coeff)
])
self.dtype = dtype = np.result_type(*fock).char
self.foo = tensor(fock[:, :nocc, :nocc], sym1)
self.fov = tensor(fock[:, :nocc, nocc:], sym1)
self.fvv = tensor(fock[:, nocc:, nocc:], sym1)
mo_energy = [fock[k].diagonal().real for k in range(nkpts)]
mo_energy = [
_adjust_occ(mo_e, nocc, -madelung)
for k, mo_e in enumerate(mo_energy)
]
mo_e_o = [e[:nocc] for e in mo_energy]
mo_e_v = [e[nocc:] + cc.level_shift for e in mo_energy]
foo_ = np.asarray([np.diag(e) for e in mo_e_o])
fvv_ = np.asarray([np.diag(e) for e in mo_e_v])
self._foo = tensor(foo_, sym1)
self._fvv = tensor(fvv_, sym1)
eia = np.zeros([nkpts, nocc, nvir])
for ki in range(nkpts):
eia[ki] = _get_epq([0, nocc, ki, mo_e_o, nonzero_opadding],
[0, nvir, ki, mo_e_v, nonzero_vpadding],
fac=[1.0, -1.0])
self.eia = tensor(eia, sym1)
self.oooo = zeros([nocc, nocc, nocc, nocc], dtype, sym2)
self.ooov = zeros([nocc, nocc, nocc, nvir], dtype, sym2)
self.ovov = zeros([nocc, nvir, nocc, nvir], dtype, sym2)
self.oovv = zeros([nocc, nocc, nvir, nvir], dtype, sym2)
self.ovvo = zeros([nocc, nvir, nvir, nocc], dtype, sym2)
self.ovvv = zeros([nocc, nvir, nvir, nvir], dtype, sym2)
self.vvvv = zeros([nvir, nvir, nvir, nvir], dtype, sym2)
self.eijab = zeros([nocc, nocc, nvir, nvir], np.float64, sym2)
with_df = cc._scf.with_df
fao2mo = cc._scf.with_df.ao2mo
kconserv = cc.khelper.kconserv
khelper = cc.khelper
jobs = list(khelper.symm_map.keys())
for itask in jobs:
ikp, ikq, ikr = itask
iks = kconserv[ikp, ikq, ikr]
eri_kpt = fao2mo(
(mo_coeff[ikp], mo_coeff[ikq], mo_coeff[ikr], mo_coeff[iks]),
(kpts[ikp], kpts[ikq], kpts[ikr], kpts[iks]),
compact=False)
if dtype == np.float: eri_kpt = eri_kpt.real
eri_kpt = eri_kpt.reshape(nmo, nmo, nmo, nmo) / nkpts
done = np.zeros([nkpts, nkpts, nkpts])
for (kp, kq, kr) in khelper.symm_map[(ikp, ikq, ikr)]:
if done[kp, kq, kr]: continue
eri_kpt_symm = khelper.transform_symm(eri_kpt, kp, kq, kr)
oooo = eri_kpt_symm[:nocc, :nocc, :nocc, :nocc]
ooov = eri_kpt_symm[:nocc, :nocc, :nocc, nocc:]
ovov = eri_kpt_symm[:nocc, nocc:, :nocc, nocc:]
oovv = eri_kpt_symm[:nocc, :nocc, nocc:, nocc:]
ovvo = eri_kpt_symm[:nocc, nocc:, nocc:, :nocc]
ovvv = eri_kpt_symm[:nocc, nocc:, nocc:, nocc:]
vvvv = eri_kpt_symm[nocc:, nocc:, nocc:, nocc:]
ks = kconserv[kp, kq, kr]
eia = _get_epq([0, nocc, kp, mo_e_o, nonzero_opadding],
[0, nvir, kq, mo_e_v, nonzero_vpadding],
fac=[1.0, -1.0])
ejb = _get_epq([0, nocc, kr, mo_e_o, nonzero_opadding],
[0, nvir, ks, mo_e_v, nonzero_vpadding],
fac=[1.0, -1.0])
eijab = eia[:, None, :, None] + ejb[None, :, None, :]
self.oooo.array[kp, kq, kr] = oooo
self.ooov.array[kp, kq, kr] = ooov
self.ovov.array[kp, kq, kr] = ovov
self.oovv.array[kp, kq, kr] = oovv
self.ovvo.array[kp, kq, kr] = ovvo
self.ovvv.array[kp, kq, kr] = ovvv
self.vvvv.array[kp, kq, kr] = vvvv
self.eijab.array[kp, kr, kq] = eijab
done[kp, kq, kr] = 1
log.timer("ao2mo transformation", *cput0)
def get_t3p2_imds_slow(cc,
t1,
t2,
eris=None,
t3p2_ip_out=None,
t3p2_ea_out=None):
"""Calculates T1, T2 amplitudes corrected by second-order T3 contribution
and intermediates used in IP/EA-CCSD(T)a
Args:
cc (:obj:`KGCCSD`):
Object containing coupled-cluster results.
t1 (:obj:`ndarray`):
T1 amplitudes.
t2 (:obj:`ndarray`):
T2 amplitudes from which the T3[2] amplitudes are formed.
eris (:obj:`_PhysicistsERIs`):
Antisymmetrized electron-repulsion integrals in physicist's notation.
t3p2_ip_out (:obj:`ndarray`):
Store results of the intermediate used in IP-EOM-CCSD(T)a.
t3p2_ea_out (:obj:`ndarray`):
Store results of the intermediate used in EA-EOM-CCSD(T)a.
Returns:
delta_ccsd (float):
Difference of perturbed and unperturbed CCSD ground-state energy,
energy(T1 + T1[2], T2 + T2[2]) - energy(T1, T2)
pt1 (:obj:`ndarray`):
Perturbatively corrected T1 amplitudes.
pt2 (:obj:`ndarray`):
Perturbatively corrected T2 amplitudes.
Reference:
D. A. Matthews, J. F. Stanton "A new approach to approximate..."
JCP 145, 124102 (2016); DOI:10.1063/1.4962910, Equation 14
Shavitt and Bartlett "Many-body Methods in Physics and Chemistry"
2009, Equation 10.33
"""
if eris is None:
eris = cc.ao2mo()
fock = eris.fock
nkpts, nocc, nvir = t1.shape
kconserv = cc.khelper.kconserv
fov = [fock[ikpt, :nocc, nocc:] for ikpt in range(nkpts)]
#foo = [fock[ikpt, :nocc, :nocc].diagonal() for ikpt in range(nkpts)]
#fvv = [fock[ikpt, nocc:, nocc:].diagonal() for ikpt in range(nkpts)]
mo_energy_occ = numpy.array(
[eris.mo_energy[ki][:nocc] for ki in range(nkpts)])
mo_energy_vir = numpy.array(
[eris.mo_energy[ki][nocc:] for ki in range(nkpts)])
# Get location of padded elements in occupied and virtual space
nonzero_opadding, nonzero_vpadding = padding_k_idx(cc, kind="split")
mo_e_o = mo_energy_occ
mo_e_v = mo_energy_vir
ccsd_energy = cc.energy(t1, t2, eris)
dtype = numpy.result_type(t1, t2)
if t3p2_ip_out is None:
t3p2_ip_out = numpy.zeros(
(nkpts, nkpts, nkpts, nocc, nvir, nocc, nocc), dtype=dtype)
Wmcik = t3p2_ip_out
if t3p2_ea_out is None:
t3p2_ea_out = numpy.zeros(
(nkpts, nkpts, nkpts, nvir, nvir, nvir, nocc), dtype=dtype)
Wacek = t3p2_ea_out
t3 = get_full_t3p2(cc, t1, t2, eris)
pt1 = numpy.zeros((nkpts, nocc, nvir), dtype=dtype)
for ki in range(nkpts):
ka = ki
for km, kn, ke in product(range(nkpts), repeat=3):
pt1[ki] += 0.25 * lib.einsum(
'mnef,imnaef->ia', eris.oovv[km, kn, ke], t3[ki, km, kn, ka,
ke])
eia = _get_epq([0, nocc, ki, mo_e_o, nonzero_opadding],
[0, nvir, ka, mo_e_v, nonzero_vpadding],
fac=[1.0, -1.0])
pt1[ki] /= eia
pt2 = numpy.zeros((nkpts, nkpts, nkpts, nocc, nocc, nvir, nvir),
dtype=dtype)
for ki, kj, ka in product(range(nkpts), repeat=3):
kb = kconserv[ki, ka, kj]
for km in range(nkpts):
pt2[ki, kj, ka] += lib.einsum('ijmabe,me->ijab', t3[ki, kj, km, ka,
kb], fov[km])
for ke in range(nkpts):
kf = kconserv[km, ke, kb]
pt2[ki, kj, ka] += 0.5 * lib.einsum(
'ijmaef,mbfe->ijab', t3[ki, kj, km, ka,
ke], eris.ovvv[km, kb, kf])
kf = kconserv[km, ke, ka]
pt2[ki, kj, ka] -= 0.5 * lib.einsum(
'ijmbef,mafe->ijab', t3[ki, kj, km, kb,
ke], eris.ovvv[km, ka, kf])
for kn in range(nkpts):
pt2[ki, kj, ka] -= 0.5 * lib.einsum(
'inmabe,nmje->ijab', t3[ki, kn, km, ka,
kb], eris.ooov[kn, km, kj])
pt2[ki, kj, ka] += 0.5 * lib.einsum(
'jnmabe,nmie->ijab', t3[kj, kn, km, ka,
kb], eris.ooov[kn, km, ki])
eia = _get_epq([0, nocc, ki, mo_e_o, nonzero_opadding],
[0, nvir, ka, mo_e_v, nonzero_vpadding],
fac=[1.0, -1.0])
ejb = _get_epq([0, nocc, kj, mo_e_o, nonzero_opadding],
[0, nvir, kb, mo_e_v, nonzero_vpadding],
fac=[1.0, -1.0])
eijab = eia[:, None, :, None] + ejb[:, None, :]
pt2[ki, kj, ka] /= eijab
pt1 += t1
pt2 += t2
for ki, kj, kk, ka, kb in product(range(nkpts), repeat=5):
kc = kpts_helper.get_kconserv3(cc._scf.cell, cc.kpts,
[ki, kj, kk, ka, kb])
tmp = t3[ki, kj, kk, ka, kb]
km = kconserv[ki, kc, kk]
ke = kconserv[ka, kk, kc]
Wmcik[km, kc, ki] += 0.5 * lib.einsum('ijkabc,mjab->mcik', tmp,
eris.oovv[km, kj, ka])
Wacek[ka, kc, ke] += -0.5 * lib.einsum('ijkabc,ijeb->acek', tmp,
eris.oovv[ki, kj, ke])
delta_ccsd_energy = cc.energy(pt1, pt2, eris) - ccsd_energy
logger.info(cc, 'CCSD energy T3[2] correction : %14.8e', delta_ccsd_energy)
return delta_ccsd_energy, pt1, pt2, Wmcik, Wacek
def kernel(mycc, eris, t1=None, t2=None, max_memory=2000, verbose=logger.INFO):
'''Returns the CCSD(T) for restricted closed-shell systems with k-points.
Note:
Returns real part of the CCSD(T) energy, raises warning if there is
a complex part.
Args:
mycc (:class:`RCCSD`): Coupled-cluster object storing results of
a coupled-cluster calculation.
eris (:class:`_ERIS`): Integral object holding the relevant electron-
repulsion integrals and Fock matrix elements
t1 (:obj:`ndarray`): t1 coupled-cluster amplitudes
t2 (:obj:`ndarray`): t2 coupled-cluster amplitudes
max_memory (float): Maximum memory used in calculation (NOT USED)
verbose (int, :class:`Logger`): verbosity of calculation
Returns:
energy_t (float): The real-part of the k-point CCSD(T) energy.
'''
assert isinstance(mycc, pyscf.pbc.cc.kccsd_rhf.RCCSD)
if isinstance(verbose, logger.Logger):
log = verbose
else:
log = logger.Logger(mycc.stdout, verbose)
if t1 is None: t1 = mycc.t1
if t2 is None: t2 = mycc.t2
if eris is None:
raise TypeError('Electron repulsion integrals, `eris`, must be passed in '
'to the CCSD(T) kernel or created in the cc object for '
'the k-point CCSD(T) to run!')
if t1 is None or t2 is None:
raise TypeError('Must pass in t1/t2 amplitudes to k-point CCSD(T)! (Maybe '
'need to run `.ccsd()` on the ccsd object?)')
cell = mycc._scf.cell
kpts = mycc.kpts
# The dtype of any local arrays that will be created
dtype = t1.dtype
nkpts, nocc, nvir = t1.shape
mo_energy_occ = [eris.mo_energy[ki][:nocc] for ki in range(nkpts)]
mo_energy_vir = [eris.mo_energy[ki][nocc:] for ki in range(nkpts)]
fov = eris.fock[:, :nocc, nocc:]
# Set up class for k-point conservation
kconserv = kpts_helper.get_kconserv(cell, kpts)
def get_w(ki, kj, kk, ka, kb, kc, a, b, c):
'''Wijkabc intermediate as described in Scuseria paper before Pijkabc acts'''
km = kconserv[ki, ka, kj]
kf = kconserv[kk, kc, kj]
ret = einsum('kjf,fi->ijk', t2[kk, kj, kc, :, :, c, :], eris.vovv[kf, ki, kb, :, :, b, a].conj())
ret = ret - einsum('mk,jim->ijk', t2[km, kk, kb, :, :, b, c], eris.ooov[kj, ki, km, :, :, :, a].conj())
return ret
def get_permuted_w(ki, kj, kk, ka, kb, kc, a, b, c):
'''Pijkabc operating on Wijkabc intermediate as described in Scuseria paper'''
ret = get_w(ki, kj, kk, ka, kb, kc, a, b, c)
ret = ret + get_w(kj, kk, ki, kb, kc, ka, b, c, a).transpose(2, 0, 1)
ret = ret + get_w(kk, ki, kj, kc, ka, kb, c, a, b).transpose(1, 2, 0)
ret = ret + get_w(ki, kk, kj, ka, kc, kb, a, c, b).transpose(0, 2, 1)
ret = ret + get_w(kk, kj, ki, kc, kb, ka, c, b, a).transpose(2, 1, 0)
ret = ret + get_w(kj, ki, kk, kb, ka, kc, b, a, c).transpose(1, 0, 2)
return ret
def get_rw(ki, kj, kk, ka, kb, kc, a, b, c):
'''R operating on Wijkabc intermediate as described in Scuseria paper'''
ret = (4. * get_permuted_w(ki, kj, kk, ka, kb, kc, a, b, c) +
1. * get_permuted_w(kk, ki, kj, ka, kb, kc, a, b, c).transpose(1, 2, 0) +
1. * get_permuted_w(kj, kk, ki, ka, kb, kc, a, b, c).transpose(2, 0, 1) -
2. * get_permuted_w(kk, kj, ki, ka, kb, kc, a, b, c).transpose(2, 1, 0) -
2. * get_permuted_w(ki, kk, kj, ka, kb, kc, a, b, c).transpose(0, 2, 1) -
2. * get_permuted_w(kj, ki, kk, ka, kb, kc, a, b, c).transpose(1, 0, 2))
return ret
def get_v(ki, kj, kk, ka, kb, kc, a, b, c):
'''Vijkabc intermediate as described in Scuseria paper'''
km = kconserv[ki, ka, kj]
kf = kconserv[ki, ka, kj]
ret = np.zeros((nocc, nocc, nocc), dtype=dtype)
if kk == kc:
ret = ret + einsum('k,ij->ijk', t1[kk, :, c], eris.oovv[ki, kj, ka, :, :, a, b].conj())
ret = ret + einsum('k,ij->ijk', fov[kk, :, c], t2[ki, kj, ka, :, :, a, b])
return ret
def get_permuted_v(ki, kj, kk, ka, kb, kc, a, b, c):
'''Pijkabc operating on Vijkabc intermediate as described in Scuseria paper'''
ret = get_v(ki, kj, kk, ka, kb, kc, a, b, c)
ret = ret + get_v(kj, kk, ki, kb, kc, ka, b, c, a).transpose(2, 0, 1)
ret = ret + get_v(kk, ki, kj, kc, ka, kb, c, a, b).transpose(1, 2, 0)
ret = ret + get_v(ki, kk, kj, ka, kc, kb, a, c, b).transpose(0, 2, 1)
ret = ret + get_v(kk, kj, ki, kc, kb, ka, c, b, a).transpose(2, 1, 0)
ret = ret + get_v(kj, ki, kk, kb, ka, kc, b, a, c).transpose(1, 0, 2)
return ret
energy_t = 0.0
# Get location of padded elements in occupied and virtual space
nonzero_opadding, nonzero_vpadding = padding_k_idx(mycc, kind="split")
for ki in range(nkpts):
for kj in range(ki + 1):
for kk in range(kj + 1):
# eigenvalue denominator: e(i) + e(j) + e(k)
eijk = LARGE_DENOM * np.ones((nocc,)*3, dtype=mo_energy_occ[0].dtype)
n0_ovp_ijk = np.ix_(nonzero_opadding[ki], nonzero_opadding[kj], nonzero_opadding[kk])
eijk[n0_ovp_ijk] = lib.direct_sum('i,j,k->ijk', mo_energy_occ[ki], mo_energy_occ[kj], mo_energy_occ[kk])[n0_ovp_ijk]
for ka in range(nkpts):
for kb in range(nkpts):
# Find momentum conservation condition for triples
# amplitude t3ijkabc
kc = kpts_helper.get_kconserv3(cell, kpts, [ki, kj, kk, ka, kb])
ia_index = ki * nkpts + ka
jb_index = kj * nkpts + kb
kc_index = kk * nkpts + kc
if not (ia_index >= jb_index and jb_index >= kc_index):
continue
# Factors to include for permutational symmetry among k-points
if (ia_index == jb_index and jb_index == kc_index):
symm_kpt = 1. # only one unique [ia, jb, kc] index
elif (ia_index == jb_index or jb_index == kc_index):
symm_kpt = 3. # three unique permutations of [ia, jb, kc]
else:
symm_kpt = 6. # six unique permutations of [ia, jb, kc]
# Determine the a, b, c indices we will loop over as
# determined by the k-point symmetry.
abc_indices = cartesian_prod([range(nvir)] * 3)
symm_3d = symm_2d_ab = symm_2d_bc = False
if ia_index == jb_index == kc_index: # ka == kb == kc
symm_3d = True
abc_indices = tril_product(range(nvir), repeat=3, tril_idx=[0, 1, 2]) # loop a >= b >= c
symm_3d = True
elif ia_index == jb_index: # ka == kb
abc_indices = tril_product(range(nvir), repeat=3, tril_idx=[0, 1]) # loop a >= b
symm_2d_ab = True
elif jb_index == kc_index:
abc_indices = tril_product(range(nvir), repeat=3, tril_idx=[1, 2]) # loop b >= c
symm_2d_bc = True
for a, b, c in abc_indices:
# Form energy denominator
# Make sure we only loop over non-frozen and/or padded elements
if( not ((a in nonzero_vpadding[ka]) and (b in nonzero_vpadding[kb]) and (c in nonzero_vpadding[kc]))):
continue
eijkabc = (eijk - mo_energy_vir[ka][a] - mo_energy_vir[kb][b] - mo_energy_vir[kc][c])
# See symm_3d and abc_indices above for description of factors
symm_abc = 1.
if symm_3d:
if a == b == c:
symm_abc = 1.
elif a == b or b == c:
symm_abc = 3.
else:
symm_abc = 6.
elif symm_2d_ab:
if a == b:
symm_abc = 1.
else:
symm_abc = 2.
elif symm_2d_bc:
if b == c:
symm_abc = 1.
else:
symm_abc = 2.
# The simplest written algorithm can be accomplished with the following four lines
#pwijk = ( get_permuted_w(ki, kj, kk, ka, kb, kc, a, b, c) +
# 0.5 * get_permuted_v(ki, kj, kk, ka, kb, kc, a, b, c) )
#rwijk = get_rw(ki, kj, kk, ka, kb, kc, a, b, c) / eijkabc
#energy_t += symm_fac * einsum('ijk,ijk', pwijk, rwijk.conj())
# Creating permuted W_ijkabc intermediate
w_int0 = get_w(ki, kj, kk, ka, kb, kc, a, b, c)
w_int1 = get_w(kj, kk, ki, kb, kc, ka, b, c, a).transpose(2, 0, 1)
w_int2 = get_w(kk, ki, kj, kc, ka, kb, c, a, b).transpose(1, 2, 0)
w_int3 = get_w(ki, kk, kj, ka, kc, kb, a, c, b).transpose(0, 2, 1)
w_int4 = get_w(kk, kj, ki, kc, kb, ka, c, b, a).transpose(2, 1, 0)
w_int5 = get_w(kj, ki, kk, kb, ka, kc, b, a, c).transpose(1, 0, 2)
# Creating permuted V_ijkabc intermediate
v_int0 = get_v(ki, kj, kk, ka, kb, kc, a, b, c)
v_int1 = get_v(kj, kk, ki, kb, kc, ka, b, c, a).transpose(2, 0, 1)
v_int2 = get_v(kk, ki, kj, kc, ka, kb, c, a, b).transpose(1, 2, 0)
v_int3 = get_v(ki, kk, kj, ka, kc, kb, a, c, b).transpose(0, 2, 1)
v_int4 = get_v(kk, kj, ki, kc, kb, ka, c, b, a).transpose(2, 1, 0)
v_int5 = get_v(kj, ki, kk, kb, ka, kc, b, a, c).transpose(1, 0, 2)
# Creating permuted W_ijkabc + 0.5 * V_ijkabc intermediate
pwijk = w_int0 + 0.5 * v_int0
pwijk += w_int1 + 0.5 * v_int1
pwijk += w_int2 + 0.5 * v_int2
pwijk += w_int3 + 0.5 * v_int3
pwijk += w_int4 + 0.5 * v_int4
pwijk += w_int5 + 0.5 * v_int5
# Creating R[W] intermediate
rwijk = np.zeros((nocc, nocc, nocc), dtype=dtype)
# Adding in contribution 4. * P[(i, j, k) -> (i, j, k)]
rwijk += 4. * w_int0
rwijk += 4. * w_int1
rwijk += 4. * w_int2
rwijk += 4. * w_int3
rwijk += 4. * w_int4
rwijk += 4. * w_int5
# Adding in contribution 1. * P[(i, j, k) -> (k, i, j)]
rwijk += 1. * get_w(kk, ki, kj, ka, kb, kc, a, b, c).transpose(1, 2, 0)
rwijk += 1. * get_w(ki, kj, kk, kb, kc, ka, b, c, a).transpose(2, 0, 1).transpose(1, 2, 0)
rwijk += 1. * get_w(kj, kk, ki, kc, ka, kb, c, a, b).transpose(1, 2, 0).transpose(1, 2, 0)
rwijk += 1. * get_w(kk, kj, ki, ka, kc, kb, a, c, b).transpose(0, 2, 1).transpose(1, 2, 0)
rwijk += 1. * get_w(kj, ki, kk, kc, kb, ka, c, b, a).transpose(2, 1, 0).transpose(1, 2, 0)
rwijk += 1. * get_w(ki, kk, kj, kb, ka, kc, b, a, c).transpose(1, 0, 2).transpose(1, 2, 0)
# Adding in contribution 1. * P[(i, j, k) -> (j, k, i)]
rwijk += 1. * get_w(kj, kk, ki, ka, kb, kc, a, b, c).transpose(2, 0, 1)
rwijk += 1. * get_w(kk, ki, kj, kb, kc, ka, b, c, a).transpose(2, 0, 1).transpose(2, 0, 1)
rwijk += 1. * get_w(ki, kj, kk, kc, ka, kb, c, a, b).transpose(1, 2, 0).transpose(2, 0, 1)
rwijk += 1. * get_w(kj, ki, kk, ka, kc, kb, a, c, b).transpose(0, 2, 1).transpose(2, 0, 1)
rwijk += 1. * get_w(ki, kk, kj, kc, kb, ka, c, b, a).transpose(2, 1, 0).transpose(2, 0, 1)
rwijk += 1. * get_w(kk, kj, ki, kb, ka, kc, b, a, c).transpose(1, 0, 2).transpose(2, 0, 1)
# Adding in contribution -2. * P[(i, j, k) -> (k, j, i)]
rwijk += -2. * get_w(kk, kj, ki, ka, kb, kc, a, b, c).transpose(2, 1, 0)
rwijk += -2. * get_w(kj, ki, kk, kb, kc, ka, b, c, a).transpose(2, 0, 1).transpose(2, 1, 0)
rwijk += -2. * get_w(ki, kk, kj, kc, ka, kb, c, a, b).transpose(1, 2, 0).transpose(2, 1, 0)
rwijk += -2. * get_w(kk, ki, kj, ka, kc, kb, a, c, b).transpose(0, 2, 1).transpose(2, 1, 0)
rwijk += -2. * get_w(ki, kj, kk, kc, kb, ka, c, b, a).transpose(2, 1, 0).transpose(2, 1, 0)
rwijk += -2. * get_w(kj, kk, ki, kb, ka, kc, b, a, c).transpose(1, 0, 2).transpose(2, 1, 0)
# Adding in contribution -2. * P[(i, j, k) -> (i, k, j)]
rwijk += -2. * get_w(ki, kk, kj, ka, kb, kc, a, b, c).transpose(0, 2, 1)
rwijk += -2. * get_w(kk, kj, ki, kb, kc, ka, b, c, a).transpose(2, 0, 1).transpose(0, 2, 1)
rwijk += -2. * get_w(kj, ki, kk, kc, ka, kb, c, a, b).transpose(1, 2, 0).transpose(0, 2, 1)
rwijk += -2. * get_w(ki, kj, kk, ka, kc, kb, a, c, b).transpose(0, 2, 1).transpose(0, 2, 1)
rwijk += -2. * get_w(kj, kk, ki, kc, kb, ka, c, b, a).transpose(2, 1, 0).transpose(0, 2, 1)
rwijk += -2. * get_w(kk, ki, kj, kb, ka, kc, b, a, c).transpose(1, 0, 2).transpose(0, 2, 1)
# Adding in contribution -2. * P[(i, j, k) -> (j, i, k)]
rwijk += -2. * get_w(kj, ki, kk, ka, kb, kc, a, b, c).transpose(1, 0, 2)
rwijk += -2. * get_w(ki, kk, kj, kb, kc, ka, b, c, a).transpose(2, 0, 1).transpose(1, 0, 2)
rwijk += -2. * get_w(kk, kj, ki, kc, ka, kb, c, a, b).transpose(1, 2, 0).transpose(1, 0, 2)
rwijk += -2. * get_w(kj, kk, ki, ka, kc, kb, a, c, b).transpose(0, 2, 1).transpose(1, 0, 2)
rwijk += -2. * get_w(kk, ki, kj, kc, kb, ka, c, b, a).transpose(2, 1, 0).transpose(1, 0, 2)
rwijk += -2. * get_w(ki, kj, kk, kb, ka, kc, b, a, c).transpose(1, 0, 2).transpose(1, 0, 2)
rwijk /= eijkabc
energy_t += symm_abc * symm_kpt * einsum('ijk,ijk', pwijk, rwijk.conj())
energy_t *= (1. / 3)
energy_t /= nkpts
if abs(energy_t.imag) > 1e-4:
log.warn('Non-zero imaginary part of CCSD(T) energy was found %s', energy_t.imag)
log.note('CCSD(T) correction per cell = %.15g', energy_t.real)
log.note('CCSD(T) correction per cell (imag) = %.15g', energy_t.imag)
return energy_t.real
def __init__(self, cis, mo_coeff=None, method="incore"):
log = logger.Logger(cis.stdout, cis.verbose)
cput0 = (time.clock(), time.time())
moidx = get_frozen_mask(cis)
cell = cis._scf.cell
nocc = cis.nocc
nmo = cis.nmo
nvir = nmo - nocc
nkpts = cis.nkpts
kpts = cis.kpts
if mo_coeff is None:
mo_coeff = cis.mo_coeff
dtype = mo_coeff[0].dtype
mo_coeff = self.mo_coeff = padded_mo_coeff(cis, mo_coeff)
# Re-make our fock MO matrix elements from density and fock AO
dm = cis._scf.make_rdm1(cis.mo_coeff, cis.mo_occ)
exxdiv = cis._scf.exxdiv if cis.keep_exxdiv else None
with lib.temporary_env(cis._scf, exxdiv=exxdiv):
# _scf.exxdiv affects eris.fock. HF exchange correction should be
# excluded from the Fock matrix.
fockao = cis._scf.get_hcore() + cis._scf.get_veff(cell, dm)
self.fock = np.asarray([
reduce(np.dot, (mo.T.conj(), fockao[k], mo))
for k, mo in enumerate(mo_coeff)
])
self.mo_energy = [self.fock[k].diagonal().real for k in range(nkpts)]
if not cis.keep_exxdiv:
# Add HFX correction in the self.mo_energy to improve convergence in
# CCSD iteration. It is useful for the 2D systems since their occupied and
# the virtual orbital energies may overlap which may lead to numerical
# issue in the CCSD iterations.
# FIXME: Whether to add this correction for other exxdiv treatments?
# Without the correction, MP2 energy may be largely off the correct value.
madelung = tools.madelung(cell, kpts)
self.mo_energy = [
_adjust_occ(mo_e, nocc, -madelung)
for k, mo_e in enumerate(self.mo_energy)
]
# Get location of padded elements in occupied and virtual space.
nocc_per_kpt = get_nocc(cis, per_kpoint=True)
nonzero_padding = padding_k_idx(cis, kind="joint")
# Check direct and indirect gaps for possible issues with CCSD convergence.
mo_e = [self.mo_energy[kp][nonzero_padding[kp]] for kp in range(nkpts)]
mo_e = np.sort([y for x in mo_e for y in x]) # Sort de-nested array
gap = mo_e[np.sum(nocc_per_kpt)] - mo_e[np.sum(nocc_per_kpt) - 1]
if gap < 1e-5:
logger.warn(
cis,
"H**O-LUMO gap %s too small for KCCSD. "
"May cause issues in convergence.",
gap,
)
memory_needed = (nkpts**3 * nocc**2 * nvir**2) * 16 / 1e6
# CIS only needs two terms: <aj|ib> and <aj|bi>; another factor of two for safety
memory_needed *= 4
memory_now = lib.current_memory()[0]
fao2mo = cis._scf.with_df.ao2mo
kconserv = cis.khelper.kconserv
khelper = cis.khelper
if cis.direct and type(cis._scf.with_df) is not df.GDF:
raise ValueError("CIS direct method must be used with GDF")
if (cis.direct and type(cis._scf.with_df) is df.GDF
and cell.dimension != 2):
# cis._scf.with_df needs to be df.GDF only (not MDF)
_init_cis_df_eris(cis, self)
else:
if (method == "incore" and
(memory_needed + memory_now < cis.max_memory)
or cell.incore_anyway):
log.info("using incore ERI storage")
self.ovov = np.empty(
(nkpts, nkpts, nkpts, nocc, nvir, nocc, nvir), dtype=dtype)
self.voov = np.empty(
(nkpts, nkpts, nkpts, nvir, nocc, nocc, nvir), dtype=dtype)
for (ikp, ikq, ikr) in khelper.symm_map.keys():
iks = kconserv[ikp, ikq, ikr]
eri_kpt = fao2mo(
(mo_coeff[ikp], mo_coeff[ikq], mo_coeff[ikr],
mo_coeff[iks]),
(kpts[ikp], kpts[ikq], kpts[ikr], kpts[iks]),
compact=False,
)
if dtype == np.float:
eri_kpt = eri_kpt.real
eri_kpt = eri_kpt.reshape(nmo, nmo, nmo, nmo)
for (kp, kq, kr) in khelper.symm_map[(ikp, ikq, ikr)]:
eri_kpt_symm = khelper.transform_symm(
eri_kpt, kp, kq, kr).transpose(0, 2, 1, 3)
self.ovov[kp, kr, kq] = (
eri_kpt_symm[:nocc, nocc:, :nocc, nocc:] / nkpts)
self.voov[kp, kr, kq] = (
eri_kpt_symm[nocc:, :nocc, :nocc, nocc:] / nkpts)
self.dtype = dtype
else:
log.info("using HDF5 ERI storage")
self.feri1 = lib.H5TmpFile()
self.ovov = self.feri1.create_dataset(
"ovov", (nkpts, nkpts, nkpts, nocc, nvir, nocc, nvir),
dtype.char)
self.voov = self.feri1.create_dataset(
"voov", (nkpts, nkpts, nkpts, nvir, nocc, nocc, nvir),
dtype.char)
# <ia|pq> = (ip|aq)
cput1 = time.clock(), time.time()
for kp in range(nkpts):
for kq in range(nkpts):
for kr in range(nkpts):
ks = kconserv[kp, kq, kr]
orbo_p = mo_coeff[kp][:, :nocc]
orbv_r = mo_coeff[kr][:, nocc:]
buf_kpt = fao2mo(
(orbo_p, mo_coeff[kq], orbv_r, mo_coeff[ks]),
(kpts[kp], kpts[kq], kpts[kr], kpts[ks]),
compact=False,
)
if mo_coeff[0].dtype == np.float:
buf_kpt = buf_kpt.real
buf_kpt = buf_kpt.reshape(nocc, nmo, nvir,
nmo).transpose(
0, 2, 1, 3)
self.dtype = buf_kpt.dtype
self.ovov[kp, kr, kq, :, :, :, :] = (
buf_kpt[:, :, :nocc, nocc:] / nkpts)
self.voov[kr, kp, ks, :, :, :, :] = (
buf_kpt[:, :, nocc:, :nocc].transpose(
1, 0, 3, 2) / nkpts)
cput1 = log.timer_debug1("transforming ovpq", *cput1)
log.timer("CIS integral transformation", *cput0)
def kernel(mycc, eris, t1=None, t2=None, max_memory=2000, verbose=logger.INFO):
'''Returns the CCSD(T) for restricted closed-shell systems with k-points.
Note:
Returns real part of the CCSD(T) energy, raises warning if there is
a complex part.
Args:
mycc (:class:`RCCSD`): Coupled-cluster object storing results of
a coupled-cluster calculation.
eris (:class:`_ERIS`): Integral object holding the relevant electron-
repulsion integrals and Fock matrix elements
t1 (:obj:`ndarray`): t1 coupled-cluster amplitudes
t2 (:obj:`ndarray`): t2 coupled-cluster amplitudes
max_memory (float): Maximum memory used in calculation (NOT USED)
verbose (int, :class:`Logger`): verbosity of calculation
Returns:
energy_t (float): The real-part of the k-point CCSD(T) energy.
'''
assert isinstance(mycc, pyscf.pbc.cc.kccsd_rhf.RCCSD)
if isinstance(verbose, logger.Logger):
log = verbose
else:
log = logger.Logger(mycc.stdout, verbose)
if t1 is None: t1 = mycc.t1
if t2 is None: t2 = mycc.t2
if eris is None:
raise TypeError(
'Electron repulsion integrals, `eris`, must be passed in '
'to the CCSD(T) kernel or created in the cc object for '
'the k-point CCSD(T) to run!')
if t1 is None or t2 is None:
raise TypeError(
'Must pass in t1/t2 amplitudes to k-point CCSD(T)! (Maybe '
'need to run `.ccsd()` on the ccsd object?)')
cell = mycc._scf.cell
kpts = mycc.kpts
# The dtype of any local arrays that will be created
dtype = t1.dtype
nkpts, nocc, nvir = t1.shape
mo_energy_occ = [eris.mo_energy[ki][:nocc] for ki in range(nkpts)]
mo_energy_vir = [eris.mo_energy[ki][nocc:] for ki in range(nkpts)]
fov = eris.fock[:, :nocc, nocc:]
# Set up class for k-point conservation
kconserv = kpts_helper.get_kconserv(cell, kpts)
def get_w(ki, kj, kk, ka, kb, kc, a, b, c):
'''Wijkabc intermediate as described in Scuseria paper before Pijkabc acts'''
km = kconserv[ki, ka, kj]
kf = kconserv[kk, kc, kj]
ret = einsum('kjf,fi->ijk', t2[kk, kj, kc, :, :, c, :],
eris.vovv[kf, ki, kb, :, :, b, a].conj())
ret = ret - einsum('mk,jim->ijk', t2[km, kk, kb, :, :, b, c],
eris.ooov[kj, ki, km, :, :, :, a].conj())
return ret
def get_permuted_w(ki, kj, kk, ka, kb, kc, a, b, c):
'''Pijkabc operating on Wijkabc intermediate as described in Scuseria paper'''
ret = get_w(ki, kj, kk, ka, kb, kc, a, b, c)
ret = ret + get_w(kj, kk, ki, kb, kc, ka, b, c, a).transpose(2, 0, 1)
ret = ret + get_w(kk, ki, kj, kc, ka, kb, c, a, b).transpose(1, 2, 0)
ret = ret + get_w(ki, kk, kj, ka, kc, kb, a, c, b).transpose(0, 2, 1)
ret = ret + get_w(kk, kj, ki, kc, kb, ka, c, b, a).transpose(2, 1, 0)
ret = ret + get_w(kj, ki, kk, kb, ka, kc, b, a, c).transpose(1, 0, 2)
return ret
def get_rw(ki, kj, kk, ka, kb, kc, a, b, c):
'''R operating on Wijkabc intermediate as described in Scuseria paper'''
ret = (
4. * get_permuted_w(ki, kj, kk, ka, kb, kc, a, b, c) + 1. *
get_permuted_w(kk, ki, kj, ka, kb, kc, a, b, c).transpose(1, 2, 0)
+ 1. * get_permuted_w(kj, kk, ki, ka, kb, kc, a, b, c).transpose(
2, 0, 1) - 2. * get_permuted_w(kk, kj, ki, ka, kb, kc, a, b,
c).transpose(2, 1, 0) -
2. * get_permuted_w(ki, kk, kj, ka, kb, kc, a, b, c).transpose(
0, 2, 1) - 2. *
get_permuted_w(kj, ki, kk, ka, kb, kc, a, b, c).transpose(1, 0, 2))
return ret
def get_v(ki, kj, kk, ka, kb, kc, a, b, c):
'''Vijkabc intermediate as described in Scuseria paper'''
km = kconserv[ki, ka, kj]
kf = kconserv[ki, ka, kj]
ret = np.zeros((nocc, nocc, nocc), dtype=dtype)
if kk == kc:
ret = ret + einsum('k,ij->ijk', t1[kk, :, c],
eris.oovv[ki, kj, ka, :, :, a, b].conj())
ret = ret + einsum('k,ij->ijk', fov[kk, :, c], t2[ki, kj, ka, :, :,
a, b])
return ret
def get_permuted_v(ki, kj, kk, ka, kb, kc, a, b, c):
'''Pijkabc operating on Vijkabc intermediate as described in Scuseria paper'''
ret = get_v(ki, kj, kk, ka, kb, kc, a, b, c)
ret = ret + get_v(kj, kk, ki, kb, kc, ka, b, c, a).transpose(2, 0, 1)
ret = ret + get_v(kk, ki, kj, kc, ka, kb, c, a, b).transpose(1, 2, 0)
ret = ret + get_v(ki, kk, kj, ka, kc, kb, a, c, b).transpose(0, 2, 1)
ret = ret + get_v(kk, kj, ki, kc, kb, ka, c, b, a).transpose(2, 1, 0)
ret = ret + get_v(kj, ki, kk, kb, ka, kc, b, a, c).transpose(1, 0, 2)
return ret
energy_t = 0.0
# Get location of padded elements in occupied and virtual space
nonzero_opadding, nonzero_vpadding = padding_k_idx(mycc, kind="split")
for ki in range(nkpts):
for kj in range(ki + 1):
for kk in range(kj + 1):
# eigenvalue denominator: e(i) + e(j) + e(k)
eijk = LARGE_DENOM * np.ones(
(nocc, ) * 3, dtype=mo_energy_occ[0].dtype)
n0_ovp_ijk = np.ix_(nonzero_opadding[ki], nonzero_opadding[kj],
nonzero_opadding[kk])
eijk[n0_ovp_ijk] = lib.direct_sum(
'i,j,k->ijk', mo_energy_occ[ki], mo_energy_occ[kj],
mo_energy_occ[kk])[n0_ovp_ijk]
for ka in range(nkpts):
for kb in range(nkpts):
# Find momentum conservation condition for triples
# amplitude t3ijkabc
kc = kpts_helper.get_kconserv3(cell, kpts,
[ki, kj, kk, ka, kb])
ia_index = ki * nkpts + ka
jb_index = kj * nkpts + kb
kc_index = kk * nkpts + kc
if not (ia_index >= jb_index and jb_index >= kc_index):
continue
# Factors to include for permutational symmetry among k-points
if (ia_index == jb_index and jb_index == kc_index):
symm_kpt = 1. # only one unique [ia, jb, kc] index
elif (ia_index == jb_index or jb_index == kc_index):
symm_kpt = 3. # three unique permutations of [ia, jb, kc]
else:
symm_kpt = 6. # six unique permutations of [ia, jb, kc]
# Determine the a, b, c indices we will loop over as
# determined by the k-point symmetry.
abc_indices = cartesian_prod([range(nvir)] * 3)
symm_3d = symm_2d_ab = symm_2d_bc = False
if ia_index == jb_index == kc_index: # ka == kb == kc
symm_3d = True
abc_indices = tril_product(
range(nvir), repeat=3,
tril_idx=[0, 1, 2]) # loop a >= b >= c
symm_3d = True
elif ia_index == jb_index: # ka == kb
abc_indices = tril_product(
range(nvir), repeat=3,
tril_idx=[0, 1]) # loop a >= b
symm_2d_ab = True
elif jb_index == kc_index:
abc_indices = tril_product(
range(nvir), repeat=3,
tril_idx=[1, 2]) # loop b >= c
symm_2d_bc = True
for a, b, c in abc_indices:
# Form energy denominator
# Make sure we only loop over non-frozen and/or padded elements
if (not ((a in nonzero_vpadding[ka]) and
(b in nonzero_vpadding[kb]) and
(c in nonzero_vpadding[kc]))):
continue
eijkabc = (eijk - mo_energy_vir[ka][a] -
mo_energy_vir[kb][b] -
mo_energy_vir[kc][c])
# See symm_3d and abc_indices above for description of factors
symm_abc = 1.
if symm_3d:
if a == b == c:
symm_abc = 1.
elif a == b or b == c:
symm_abc = 3.
else:
symm_abc = 6.
elif symm_2d_ab:
if a == b:
symm_abc = 1.
else:
symm_abc = 2.
elif symm_2d_bc:
if b == c:
symm_abc = 1.
else:
symm_abc = 2.
# The simplest written algorithm can be accomplished with the following four lines
#pwijk = ( get_permuted_w(ki, kj, kk, ka, kb, kc, a, b, c) +
# 0.5 * get_permuted_v(ki, kj, kk, ka, kb, kc, a, b, c) )
#rwijk = get_rw(ki, kj, kk, ka, kb, kc, a, b, c) / eijkabc
#energy_t += symm_fac * einsum('ijk,ijk', pwijk, rwijk.conj())
# Creating permuted W_ijkabc intermediate
w_int0 = get_w(ki, kj, kk, ka, kb, kc, a, b, c)
w_int1 = get_w(kj, kk, ki, kb, kc, ka, b, c,
a).transpose(2, 0, 1)
w_int2 = get_w(kk, ki, kj, kc, ka, kb, c, a,
b).transpose(1, 2, 0)
w_int3 = get_w(ki, kk, kj, ka, kc, kb, a, c,
b).transpose(0, 2, 1)
w_int4 = get_w(kk, kj, ki, kc, kb, ka, c, b,
a).transpose(2, 1, 0)
w_int5 = get_w(kj, ki, kk, kb, ka, kc, b, a,
c).transpose(1, 0, 2)
# Creating permuted V_ijkabc intermediate
v_int0 = get_v(ki, kj, kk, ka, kb, kc, a, b, c)
v_int1 = get_v(kj, kk, ki, kb, kc, ka, b, c,
a).transpose(2, 0, 1)
v_int2 = get_v(kk, ki, kj, kc, ka, kb, c, a,
b).transpose(1, 2, 0)
v_int3 = get_v(ki, kk, kj, ka, kc, kb, a, c,
b).transpose(0, 2, 1)
v_int4 = get_v(kk, kj, ki, kc, kb, ka, c, b,
a).transpose(2, 1, 0)
v_int5 = get_v(kj, ki, kk, kb, ka, kc, b, a,
c).transpose(1, 0, 2)
# Creating permuted W_ijkabc + 0.5 * V_ijkabc intermediate
pwijk = w_int0 + 0.5 * v_int0
pwijk += w_int1 + 0.5 * v_int1
pwijk += w_int2 + 0.5 * v_int2
pwijk += w_int3 + 0.5 * v_int3
pwijk += w_int4 + 0.5 * v_int4
pwijk += w_int5 + 0.5 * v_int5
# Creating R[W] intermediate
rwijk = np.zeros((nocc, nocc, nocc), dtype=dtype)
# Adding in contribution 4. * P[(i, j, k) -> (i, j, k)]
rwijk += 4. * w_int0
rwijk += 4. * w_int1
rwijk += 4. * w_int2
rwijk += 4. * w_int3
rwijk += 4. * w_int4
rwijk += 4. * w_int5
# Adding in contribution 1. * P[(i, j, k) -> (k, i, j)]
rwijk += 1. * get_w(kk, ki, kj, ka, kb, kc, a, b,
c).transpose(1, 2, 0)
rwijk += 1. * get_w(
ki, kj, kk, kb, kc, ka, b, c, a).transpose(
2, 0, 1).transpose(1, 2, 0)
rwijk += 1. * get_w(
kj, kk, ki, kc, ka, kb, c, a, b).transpose(
1, 2, 0).transpose(1, 2, 0)
rwijk += 1. * get_w(
kk, kj, ki, ka, kc, kb, a, c, b).transpose(
0, 2, 1).transpose(1, 2, 0)
rwijk += 1. * get_w(
kj, ki, kk, kc, kb, ka, c, b, a).transpose(
2, 1, 0).transpose(1, 2, 0)
rwijk += 1. * get_w(
ki, kk, kj, kb, ka, kc, b, a, c).transpose(
1, 0, 2).transpose(1, 2, 0)
# Adding in contribution 1. * P[(i, j, k) -> (j, k, i)]
rwijk += 1. * get_w(kj, kk, ki, ka, kb, kc, a, b,
c).transpose(2, 0, 1)
rwijk += 1. * get_w(
kk, ki, kj, kb, kc, ka, b, c, a).transpose(
2, 0, 1).transpose(2, 0, 1)
rwijk += 1. * get_w(
ki, kj, kk, kc, ka, kb, c, a, b).transpose(
1, 2, 0).transpose(2, 0, 1)
rwijk += 1. * get_w(
kj, ki, kk, ka, kc, kb, a, c, b).transpose(
0, 2, 1).transpose(2, 0, 1)
rwijk += 1. * get_w(
ki, kk, kj, kc, kb, ka, c, b, a).transpose(
2, 1, 0).transpose(2, 0, 1)
rwijk += 1. * get_w(
kk, kj, ki, kb, ka, kc, b, a, c).transpose(
1, 0, 2).transpose(2, 0, 1)
# Adding in contribution -2. * P[(i, j, k) -> (k, j, i)]
rwijk += -2. * get_w(kk, kj, ki, ka, kb, kc, a, b,
c).transpose(2, 1, 0)
rwijk += -2. * get_w(
kj, ki, kk, kb, kc, ka, b, c, a).transpose(
2, 0, 1).transpose(2, 1, 0)
rwijk += -2. * get_w(
ki, kk, kj, kc, ka, kb, c, a, b).transpose(
1, 2, 0).transpose(2, 1, 0)
rwijk += -2. * get_w(
kk, ki, kj, ka, kc, kb, a, c, b).transpose(
0, 2, 1).transpose(2, 1, 0)
rwijk += -2. * get_w(
ki, kj, kk, kc, kb, ka, c, b, a).transpose(
2, 1, 0).transpose(2, 1, 0)
rwijk += -2. * get_w(
kj, kk, ki, kb, ka, kc, b, a, c).transpose(
1, 0, 2).transpose(2, 1, 0)
# Adding in contribution -2. * P[(i, j, k) -> (i, k, j)]
rwijk += -2. * get_w(ki, kk, kj, ka, kb, kc, a, b,
c).transpose(0, 2, 1)
rwijk += -2. * get_w(
kk, kj, ki, kb, kc, ka, b, c, a).transpose(
2, 0, 1).transpose(0, 2, 1)
rwijk += -2. * get_w(
kj, ki, kk, kc, ka, kb, c, a, b).transpose(
1, 2, 0).transpose(0, 2, 1)
rwijk += -2. * get_w(
ki, kj, kk, ka, kc, kb, a, c, b).transpose(
0, 2, 1).transpose(0, 2, 1)
rwijk += -2. * get_w(
kj, kk, ki, kc, kb, ka, c, b, a).transpose(
2, 1, 0).transpose(0, 2, 1)
rwijk += -2. * get_w(
kk, ki, kj, kb, ka, kc, b, a, c).transpose(
1, 0, 2).transpose(0, 2, 1)
# Adding in contribution -2. * P[(i, j, k) -> (j, i, k)]
rwijk += -2. * get_w(kj, ki, kk, ka, kb, kc, a, b,
c).transpose(1, 0, 2)
rwijk += -2. * get_w(
ki, kk, kj, kb, kc, ka, b, c, a).transpose(
2, 0, 1).transpose(1, 0, 2)
rwijk += -2. * get_w(
kk, kj, ki, kc, ka, kb, c, a, b).transpose(
1, 2, 0).transpose(1, 0, 2)
rwijk += -2. * get_w(
kj, kk, ki, ka, kc, kb, a, c, b).transpose(
0, 2, 1).transpose(1, 0, 2)
rwijk += -2. * get_w(
kk, ki, kj, kc, kb, ka, c, b, a).transpose(
2, 1, 0).transpose(1, 0, 2)
rwijk += -2. * get_w(
ki, kj, kk, kb, ka, kc, b, a, c).transpose(
1, 0, 2).transpose(1, 0, 2)
rwijk /= eijkabc
energy_t += symm_abc * symm_kpt * einsum(
'ijk,ijk', pwijk, rwijk.conj())
energy_t *= (1. / 3)
energy_t /= nkpts
if abs(energy_t.imag) > 1e-4:
log.warn('Non-zero imaginary part of CCSD(T) energy was found %s',
energy_t.imag)
log.note('CCSD(T) correction per cell = %.15g', energy_t.real)
log.note('CCSD(T) correction per cell (imag) = %.15g', energy_t.imag)
return energy_t.real
