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Copy pathuadc_ea.py
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2609 lines (2132 loc) · 125 KB
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# Copyright 2014-2022 The PySCF Developers. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
# Author: Abdelrahman Ahmed <>
# Samragni Banerjee <samragnibanerjee4@gmail.com>
# James Serna <jamcar456@gmail.com>
# Terrence Stahl <>
# Ning-Yuan Chen <cny003@outlook.com>
# Alexander Sokolov <alexander.y.sokolov@gmail.com>
#
'''
Unrestricted algebraic diagrammatic construction
'''
import numpy as np
from pyscf import lib, symm
from pyscf.lib import logger
from pyscf.adc import uadc
from pyscf.adc import uadc_ao2mo
from pyscf.adc import radc_ao2mo
from pyscf.adc import dfadc
from pyscf.data.nist import HARTREE2EV
def get_imds(adc, eris=None):
cput0 = (logger.process_clock(), logger.perf_counter())
log = logger.Logger(adc.stdout, adc.verbose)
if adc.method not in ("adc(2)", "adc(2)-x", "adc(3)"):
raise NotImplementedError(adc.method)
method = adc.method
t1 = adc.t1
t2 = adc.t2
nocc_a = adc.nocc_a
nocc_b = adc.nocc_b
nvir_a = adc.nvir_a
nvir_b = adc.nvir_b
ab_ind_a = np.tril_indices(nvir_a, k=-1)
ab_ind_b = np.tril_indices(nvir_b, k=-1)
e_vir_a = adc.mo_energy_a[nocc_a:]
e_vir_b = adc.mo_energy_b[nocc_b:]
idn_vir_a = np.identity(nvir_a)
idn_vir_b = np.identity(nvir_b)
if eris is None:
eris = adc.transform_integrals()
eris_ovvo = eris.ovvo
eris_OVVO = eris.OVVO
eris_ovVO = eris.ovVO
eris_OVvo = eris.OVvo
# a-b block
# Zeroth-order terms
M_ab_a = lib.einsum('ab,a->ab', idn_vir_a, e_vir_a)
M_ab_b = lib.einsum('ab,a->ab', idn_vir_b, e_vir_b)
# Second-order terms
t2_1_a = t2[0][0][:]
M_ab_a -= 0.5 * 0.5 * lib.einsum('lmad,lbdm->ab',t2_1_a, eris_ovvo,optimize=True)
M_ab_a += 0.5 * 0.5 * lib.einsum('lmad,ldbm->ab',t2_1_a, eris_ovvo,optimize=True)
M_ab_a -= 0.5 * 0.5 * lib.einsum('lmbd,ladm->ab',t2_1_a,eris_ovvo,optimize=True)
M_ab_a += 0.5 * 0.5 * lib.einsum('lmbd,ldam->ab',t2_1_a, eris_ovvo,optimize=True)
del t2_1_a
t2_1_b = t2[0][2][:]
M_ab_b -= 0.5 * 0.5 * lib.einsum('lmad,lbdm->ab',t2_1_b, eris_OVVO,optimize=True)
M_ab_b += 0.5 * 0.5 * lib.einsum('lmad,ldbm->ab',t2_1_b, eris_OVVO,optimize=True)
M_ab_b -= 0.5 * 0.5 * lib.einsum('lmbd,ladm->ab',t2_1_b, eris_OVVO,optimize=True)
M_ab_b += 0.5 * 0.5 * lib.einsum('lmbd,ldam->ab',t2_1_b, eris_OVVO,optimize=True)
del t2_1_b
t2_1_ab = t2[0][1][:]
M_ab_a -= 0.5 * lib.einsum('lmad,lbdm->ab',t2_1_ab, eris_ovVO,optimize=True)
M_ab_b -= 0.5 * lib.einsum('mlda,mdbl->ab',t2_1_ab, eris_ovVO,optimize=True)
M_ab_a -= 0.5 * lib.einsum('lmbd,ladm->ab',t2_1_ab, eris_ovVO,optimize=True)
M_ab_b -= 0.5 * lib.einsum('mldb,mdal->ab',t2_1_ab, eris_ovVO,optimize=True)
del t2_1_ab
cput0 = log.timer_debug1("Completed M_ab second-order terms ADC(2) calculation", *cput0)
#Third-order terms
if (method =='adc(3)'):
t1_2_a, t1_2_b = t1[0]
eris_oovv = eris.oovv
eris_OOVV = eris.OOVV
eris_OOvv = eris.OOvv
eris_ooVV = eris.ooVV
eris_ovvo = eris.ovvo
eris_OVVO = eris.OVVO
eris_OVvo = eris.OVvo
eris_ovVO = eris.ovVO
if eris.ovvv is None:
chnk_size = uadc_ao2mo.calculate_chunk_size(adc)
for a,b in lib.prange(0,nocc_a,chnk_size):
eris_ovvv = dfadc.get_ovvv_spin_df(
adc, eris.Lov, eris.Lvv, a, chnk_size).reshape(-1,nvir_a,nvir_a,nvir_a)
M_ab_a += lib.einsum('ld,ldab->ab',t1_2_a[a:b], eris_ovvv,optimize=True)
M_ab_a -= lib.einsum('ld,lbad->ab',t1_2_a[a:b], eris_ovvv,optimize=True)
M_ab_a += lib.einsum('ld,ldab->ab',t1_2_a[a:b], eris_ovvv,optimize=True)
M_ab_a -= lib.einsum('ld,ladb->ab',t1_2_a[a:b], eris_ovvv,optimize=True)
del eris_ovvv
else :
eris_ovvv = radc_ao2mo.unpack_eri_1(eris.ovvv, nvir_a)
k = eris_ovvv.shape[0]
M_ab_a += lib.einsum('ld,ldab->ab',t1_2_a, eris_ovvv,optimize=True)
M_ab_a -= lib.einsum('ld,lbad->ab',t1_2_a, eris_ovvv,optimize=True)
M_ab_a += lib.einsum('ld,ldab->ab',t1_2_a, eris_ovvv,optimize=True)
M_ab_a -= lib.einsum('ld,ladb->ab',t1_2_a, eris_ovvv,optimize=True)
del eris_ovvv
if eris.OVvv is None:
chnk_size = uadc_ao2mo.calculate_chunk_size(adc)
for a,b in lib.prange(0,nocc_b,chnk_size):
eris_OVvv = dfadc.get_ovvv_spin_df(
adc, eris.LOV, eris.Lvv, a, chnk_size).reshape(-1,nvir_b,nvir_a,nvir_a)
M_ab_a += lib.einsum('ld,ldab->ab',t1_2_b[a:b], eris_OVvv,optimize=True)
M_ab_a += lib.einsum('ld,ldab->ab',t1_2_b[a:b], eris_OVvv,optimize=True)
del eris_OVvv
else :
eris_OVvv = radc_ao2mo.unpack_eri_1(eris.OVvv, nvir_a)
M_ab_a += lib.einsum('ld,ldab->ab',t1_2_b, eris_OVvv,optimize=True)
M_ab_a += lib.einsum('ld,ldab->ab',t1_2_b, eris_OVvv,optimize=True)
del eris_OVvv
if eris.OVVV is None:
chnk_size = uadc_ao2mo.calculate_chunk_size(adc)
for a,b in lib.prange(0,nocc_b,chnk_size):
eris_OVVV = dfadc.get_ovvv_spin_df(
adc, eris.LOV, eris.LVV, a, chnk_size).reshape(-1,nvir_b,nvir_b,nvir_b)
M_ab_b += lib.einsum('ld,ldab->ab',t1_2_b[a:b], eris_OVVV,optimize=True)
M_ab_b -= lib.einsum('ld,lbad->ab',t1_2_b[a:b], eris_OVVV,optimize=True)
M_ab_b += lib.einsum('ld,ldab->ab',t1_2_b[a:b], eris_OVVV,optimize=True)
M_ab_b -= lib.einsum('ld,ladb->ab',t1_2_b[a:b], eris_OVVV,optimize=True)
del eris_OVVV
else :
eris_OVVV = radc_ao2mo.unpack_eri_1(eris.OVVV, nvir_b)
M_ab_b += lib.einsum('ld,ldab->ab',t1_2_b, eris_OVVV,optimize=True)
M_ab_b -= lib.einsum('ld,lbad->ab',t1_2_b, eris_OVVV,optimize=True)
M_ab_b += lib.einsum('ld,ldab->ab',t1_2_b, eris_OVVV,optimize=True)
M_ab_b -= lib.einsum('ld,ladb->ab',t1_2_b, eris_OVVV,optimize=True)
del eris_OVVV
if eris.ovVV is None:
chnk_size = uadc_ao2mo.calculate_chunk_size(adc)
for a,b in lib.prange(0,nocc_a,chnk_size):
eris_ovVV = dfadc.get_ovvv_spin_df(
adc, eris.Lov, eris.LVV, a, chnk_size).reshape(-1,nvir_a,nvir_b,nvir_b)
M_ab_b += lib.einsum('ld,ldab->ab',t1_2_a[a:b], eris_ovVV,optimize=True)
M_ab_b += lib.einsum('ld,ldab->ab',t1_2_a[a:b], eris_ovVV,optimize=True)
del eris_ovVV
else :
eris_ovVV = radc_ao2mo.unpack_eri_1(eris.ovVV, nvir_b)
k = eris_ovVV.shape[0]
M_ab_b += lib.einsum('ld,ldab->ab',t1_2_a, eris_ovVV,optimize=True)
M_ab_b += lib.einsum('ld,ldab->ab',t1_2_a, eris_ovVV,optimize=True)
del eris_ovVV
cput0 = log.timer_debug1("Completed M_ab ovvv ADC(3) calculation", *cput0)
t2_2_a = t2[1][0][:]
M_ab_a -= 0.5 * 0.5 * lib.einsum('lmad,lbdm->ab',t2_2_a, eris_ovvo,optimize=True)
M_ab_a += 0.5 * 0.5 * lib.einsum('lmad,ldbm->ab',t2_2_a, eris_ovvo,optimize=True)
M_ab_a -= 0.5 * 0.5 * lib.einsum('lmbd,ladm->ab',t2_2_a,eris_ovvo,optimize=True)
M_ab_a += 0.5 * 0.5 * lib.einsum('lmbd,ldam->ab',t2_2_a, eris_ovvo,optimize=True)
t2_2_b = t2[1][2][:]
M_ab_b -= 0.5 * 0.5 * lib.einsum('lmad,lbdm->ab',t2_2_b, eris_OVVO,optimize=True)
M_ab_b += 0.5 * 0.5 * lib.einsum('lmad,ldbm->ab',t2_2_b, eris_OVVO,optimize=True)
M_ab_b -= 0.5 * 0.5 * lib.einsum('lmbd,ladm->ab',t2_2_b, eris_OVVO,optimize=True)
M_ab_b += 0.5 * 0.5 * lib.einsum('lmbd,ldam->ab',t2_2_b, eris_OVVO,optimize=True)
t2_2_ab = t2[1][1][:]
M_ab_a -= 0.5 * lib.einsum('lmad,lbdm->ab',t2_2_ab, eris_ovVO,optimize=True)
M_ab_b -= 0.5 * lib.einsum('mlda,mdbl->ab',t2_2_ab, eris_ovVO,optimize=True)
M_ab_a -= 0.5 * lib.einsum('lmbd,ladm->ab',t2_2_ab, eris_ovVO,optimize=True)
M_ab_b -= 0.5 * lib.einsum('mldb,mdal->ab',t2_2_ab, eris_ovVO,optimize=True)
t2_1_a = t2[0][0][:]
t2_1_ab = t2[0][1][:]
M_ab_a -= 0.5 * lib.einsum('lnde,mlbd,neam->ab',t2_1_ab, t2_1_a, eris_OVvo, optimize=True)
M_ab_a += 0.5 * lib.einsum('lned,lmbd,nmae->ab',t2_1_ab, t2_1_ab, eris_OOvv, optimize=True)
M_ab_t = lib.einsum('lned,mlbd->nemb', t2_1_a,t2_1_a, optimize=True)
M_ab_a -= 0.5 * lib.einsum('nemb,nmae->ab',M_ab_t, eris_oovv, optimize=True)
M_ab_a += 0.5 * lib.einsum('nemb,maen->ab',M_ab_t, eris_ovvo, optimize=True)
M_ab_a -= 0.5 * lib.einsum('name,nmeb->ab',M_ab_t, eris_oovv, optimize=True)
M_ab_a += 0.5 * lib.einsum('name,nbem->ab',M_ab_t, eris_ovvo, optimize=True)
del M_ab_t
M_ab_t = lib.einsum('nled,mlbd->nemb', t2_1_ab,t2_1_ab, optimize=True)
M_ab_a += 0.5 * lib.einsum('nemb,nmae->ab',M_ab_t, eris_oovv, optimize=True)
M_ab_a -= 0.5 * lib.einsum('nemb,maen->ab',M_ab_t, eris_ovvo, optimize=True)
del M_ab_t
M_ab_t = lib.einsum('lnde,lmdb->nemb', t2_1_ab,t2_1_ab, optimize=True)
M_ab_b += 0.5 * lib.einsum('nemb,nmae->ab',M_ab_t, eris_OOVV, optimize=True)
M_ab_b -= 0.5 * lib.einsum('nemb,maen->ab',M_ab_t, eris_OVVO, optimize=True)
del M_ab_t
M_ab_b += 0.5 * lib.einsum('lned,lmdb,neam->ab',t2_1_a, t2_1_ab, eris_ovVO, optimize=True)
M_ab_b += 0.5 * lib.einsum('nlde,mldb,nmae->ab',t2_1_ab, t2_1_ab, eris_ooVV, optimize=True)
M_ab_a += 0.5 * lib.einsum('mled,nlad,nmeb->ab',t2_1_ab, t2_1_ab, eris_oovv, optimize=True)
M_ab_a -= 0.5 * lib.einsum('mled,nlad,nbem->ab',t2_1_ab, t2_1_ab, eris_ovvo, optimize=True)
M_ab_a += 0.5 * lib.einsum('lmed,lnad,nmeb->ab',t2_1_ab, t2_1_ab, eris_OOvv, optimize=True)
M_ab_a += 0.5 * lib.einsum('lmde,lnad,nbem->ab',t2_1_ab, t2_1_a, eris_ovVO, optimize=True)
M_ab_b += 0.5 * lib.einsum('lmde,lnda,nmeb->ab',t2_1_ab, t2_1_ab, eris_OOVV, optimize=True)
M_ab_b -= 0.5 * lib.einsum('lmde,lnda,nbem->ab',t2_1_ab, t2_1_ab, eris_OVVO, optimize=True)
M_ab_b += 0.5 * lib.einsum('mlde,nlda,nmeb->ab',t2_1_ab, t2_1_ab, eris_ooVV, optimize=True)
M_ab_b -= 0.5 * lib.einsum('mled,lnda,nbem->ab',t2_1_a, t2_1_ab, eris_OVvo, optimize=True)
M_ab_a += 0.5*lib.einsum('lned,mled,nmab->ab',t2_1_a, t2_1_a, eris_oovv, optimize=True)
M_ab_a -= 0.5*lib.einsum('lned,mled,nbam->ab',t2_1_a, t2_1_a, eris_ovvo, optimize=True)
M_ab_a -= lib.einsum('nled,mled,nmab->ab',t2_1_ab, t2_1_ab, eris_oovv, optimize=True)
M_ab_a += lib.einsum('nled,mled,nbam->ab',t2_1_ab, t2_1_ab, eris_ovvo, optimize=True)
M_ab_a -= lib.einsum('lned,lmed,nmab->ab',t2_1_ab, t2_1_ab, eris_OOvv, optimize=True)
M_ab_b -= lib.einsum('lned,lmed,nmab->ab',t2_1_ab, t2_1_ab, eris_OOVV, optimize=True)
M_ab_b += lib.einsum('lned,lmed,nbam->ab',t2_1_ab, t2_1_ab, eris_OVVO, optimize=True)
M_ab_b += 0.5*lib.einsum('lned,mled,nmab->ab',t2_1_a, t2_1_a, eris_ooVV, optimize=True)
M_ab_b -= lib.einsum('nled,mled,nmab->ab',t2_1_ab, t2_1_ab, eris_ooVV, optimize=True)
t2_1_b = t2[0][2][:]
M_ab_a += 0.5 * lib.einsum('lned,mlbd,neam->ab',t2_1_b, t2_1_ab, eris_OVvo, optimize=True)
M_ab_t = lib.einsum('lned,mlbd->nemb', t2_1_b,t2_1_b, optimize=True)
M_ab_b -= 0.5 * lib.einsum('nemb,nmae->ab',M_ab_t, eris_OOVV, optimize=True)
M_ab_b += 0.5 * lib.einsum('nemb,maen->ab',M_ab_t, eris_OVVO, optimize=True)
M_ab_b -= 0.5 * lib.einsum('name,nmeb->ab',M_ab_t, eris_OOVV, optimize=True)
M_ab_b += 0.5 * lib.einsum('name,nbem->ab',M_ab_t, eris_OVVO, optimize=True)
del M_ab_t
M_ab_b -= 0.5 * lib.einsum('nled,mlbd,neam->ab',t2_1_ab, t2_1_b, eris_ovVO, optimize=True)
M_ab_a -= 0.5 * lib.einsum('mled,nlad,nbem->ab',t2_1_b, t2_1_ab, eris_ovVO, optimize=True)
M_ab_b += 0.5 * lib.einsum('mled,lnad,nbem->ab',t2_1_ab, t2_1_b, eris_OVvo, optimize=True)
M_ab_a += 0.5 * lib.einsum('lned,mled,nmab->ab',t2_1_b, t2_1_b, eris_OOvv, optimize=True)
M_ab_b += 0.5 * lib.einsum('lned,mled,nmab->ab',t2_1_b, t2_1_b, eris_OOVV, optimize=True)
M_ab_b -= 0.5 * lib.einsum('lned,mled,nbam->ab',t2_1_b, t2_1_b, eris_OVVO, optimize=True)
log.timer_debug1("Completed M_ab ADC(3) small integrals calculation")
t2_1_a = t2[0][0][:]
t2_1_ab = t2[0][1][:]
if isinstance(eris.vvvv_p,np.ndarray):
eris_vvvv = radc_ao2mo.unpack_eri_2(eris.vvvv_p, nvir_a)
M_ab_a -= 0.5 * 0.25*lib.einsum('mlef,mlbd,adef->ab',
t2_1_a, t2_1_a, eris_vvvv, optimize=True)
M_ab_a -= 0.5*lib.einsum('mldf,mled,aebf->ab',t2_1_a, t2_1_a, eris_vvvv, optimize=True)
M_ab_a += lib.einsum('mlfd,mled,aebf->ab',t2_1_ab, t2_1_ab, eris_vvvv, optimize=True)
del eris_vvvv
M_ab_a -= 2 * 0.5 * 0.25*lib.einsum('mlaf,mlbf->ab',
t2_1_a, adc.imds.t2_1_vvvv[0], optimize=True)
else:
M_ab_a -= 2*0.5*0.25*lib.einsum('mlad,mlbd->ab',
adc.imds.t2_1_vvvv[0], t2_1_a, optimize=True)
M_ab_a -= 2*0.5*0.25*lib.einsum('mlaf,mlbf->ab', t2_1_a,
adc.imds.t2_1_vvvv[0], optimize=True)
if isinstance(eris.vvvv_p, list):
a = 0
temp = np.zeros((nvir_a,nvir_a))
for dataset in eris.vvvv_p:
k = dataset.shape[0]
vvvv = dataset[:]
eris_vvvv = np.zeros((k,nvir_a,nvir_a,nvir_a))
eris_vvvv[:,:,ab_ind_a[0],ab_ind_a[1]] = vvvv
eris_vvvv[:,:,ab_ind_a[1],ab_ind_a[0]] = -vvvv
temp[a:a+k] -= 0.5*lib.einsum('mldf,mled,aebf->ab',
t2_1_a, t2_1_a, eris_vvvv, optimize=True)
temp[a:a+k] += lib.einsum('mlfd,mled,aebf->ab',t2_1_ab,
t2_1_ab, eris_vvvv, optimize=True)
del eris_vvvv
a += k
M_ab_a += temp
a = 0
temp = np.zeros((nvir_b,nvir_b))
for dataset in eris.VvVv_p:
k = dataset.shape[0]
eris_VvVv = dataset[:].reshape(-1,nvir_a,nvir_b,nvir_a)
temp[a:a+k] -= 0.5*lib.einsum('mldf,mled,aebf->ab',
t2_1_a, t2_1_a, eris_VvVv, optimize=True)
temp[a:a+k] += lib.einsum('mlfd,mled,aebf->ab',t2_1_ab,
t2_1_ab, eris_VvVv, optimize=True)
a += k
M_ab_b += temp
elif eris.vvvv_p is None:
temp = np.zeros((nvir_a,nvir_a))
chnk_size = uadc_ao2mo.calculate_chunk_size(adc)
for a,b in lib.prange(0,nvir_a,chnk_size):
vvvv = dfadc.get_vvvv_antisym_df(adc, eris.Lvv, a, chnk_size)
eris_vvvv = np.zeros((vvvv.shape[0],nvir_a,nvir_a,nvir_a))
eris_vvvv[:,:,ab_ind_a[0],ab_ind_a[1]] = vvvv
eris_vvvv[:,:,ab_ind_a[1],ab_ind_a[0]] = -vvvv
temp[a:b] -= 0.5*lib.einsum('mldf,mled,aebf->ab',
t2_1_a, t2_1_a, eris_vvvv, optimize=True)
temp[a:b] += lib.einsum('mlfd,mled,aebf->ab',t2_1_ab,
t2_1_ab, eris_vvvv, optimize=True)
del eris_vvvv
M_ab_a += temp
del temp
temp = np.zeros((nvir_b,nvir_b))
for a,b in lib.prange(0,nvir_b,chnk_size):
eris_VvVv = dfadc.get_vVvV_df(adc, eris.LVV, eris.Lvv, a, chnk_size)
temp[a:b] -= 0.5*lib.einsum('mldf,mled,aebf->ab',
t2_1_a, t2_1_a, eris_VvVv, optimize=True)
temp[a:b] += lib.einsum('mlfd,mled,aebf->ab',t2_1_ab,
t2_1_ab, eris_VvVv, optimize=True)
M_ab_b += temp
del temp
t2_1_b = t2[0][2][:]
if isinstance(eris.vVvV_p,np.ndarray):
eris_vVvV = eris.vVvV_p
eris_vVvV = eris_vVvV.reshape(nvir_a,nvir_b,nvir_a,nvir_b)
M_ab_a -= 0.5*lib.einsum('mlef,mlbd,adef->ab',t2_1_ab,
t2_1_ab, eris_vVvV, optimize=True)
M_ab_a -= 0.5*lib.einsum('mldf,mled,aebf->ab',t2_1_b, t2_1_b, eris_vVvV, optimize=True)
M_ab_a += lib.einsum('mldf,mlde,aebf->ab',t2_1_ab, t2_1_ab, eris_vVvV, optimize=True)
M_ab_b -= 0.5*lib.einsum('mlef,mldb,daef->ab',t2_1_ab,
t2_1_ab, eris_vVvV, optimize=True)
M_ab_b -= 0.5*lib.einsum('mldf,mled,eafb->ab',t2_1_a, t2_1_a, eris_vVvV, optimize=True)
M_ab_b += lib.einsum('mlfd,mled,eafb->ab',t2_1_ab, t2_1_ab, eris_vVvV, optimize=True)
eris_vVvV = eris_vVvV.reshape(nvir_a*nvir_b,nvir_a*nvir_b)
M_ab_a -= 0.5*lib.einsum('mlaf,mlbf->ab',t2_1_ab, adc.imds.t2_1_vvvv[1], optimize=True)
M_ab_b -= 0.5*lib.einsum('mlfa,mlfb->ab',t2_1_ab, adc.imds.t2_1_vvvv[1], optimize=True)
else:
M_ab_a -= 0.5 * lib.einsum('mlad,mlbd->ab',
adc.imds.t2_1_vvvv[1], t2_1_ab, optimize=True)
M_ab_b -= 0.5 * lib.einsum('mlda,mldb->ab',
adc.imds.t2_1_vvvv[1], t2_1_ab, optimize=True)
M_ab_a -= 0.5 * lib.einsum('mlaf,mlbf->ab', t2_1_ab,
adc.imds.t2_1_vvvv[1], optimize=True)
M_ab_b -= 0.5 * lib.einsum('mlfa,mlfb->ab', t2_1_ab,
adc.imds.t2_1_vvvv[1], optimize=True)
del t2_1_a
if isinstance(eris.VVVV_p,np.ndarray):
eris_VVVV = radc_ao2mo.unpack_eri_2(eris.VVVV_p, nvir_b)
M_ab_b -= 0.5*0.25*lib.einsum('mlef,mlbd,adef->ab',t2_1_b,
t2_1_b, eris_VVVV, optimize=True)
M_ab_b -= 0.5*lib.einsum('mldf,mled,aebf->ab',t2_1_b, t2_1_b, eris_VVVV, optimize=True)
M_ab_b += lib.einsum('mldf,mlde,aebf->ab',t2_1_ab, t2_1_ab, eris_VVVV, optimize=True)
del eris_VVVV
M_ab_b -= 2 * 0.5 * 0.25*lib.einsum('mlaf,mlbf->ab',
t2_1_b, adc.imds.t2_1_vvvv[2], optimize=True)
else:
M_ab_b -= 2 * 0.5 * 0.25*lib.einsum('mlad,mlbd->ab',
adc.imds.t2_1_vvvv[2], t2_1_b, optimize=True)
M_ab_b -= 2 * 0.5 * 0.25*lib.einsum('mlaf,mlbf->ab',
t2_1_b, adc.imds.t2_1_vvvv[2], optimize=True)
if isinstance(eris.vvvv_p, list):
a = 0
temp = np.zeros((nvir_b,nvir_b))
for dataset in eris.VVVV_p:
k = dataset.shape[0]
VVVV = dataset[:]
eris_VVVV = np.zeros((k,nvir_b,nvir_b,nvir_b))
eris_VVVV[:,:,ab_ind_b[0],ab_ind_b[1]] = VVVV
eris_VVVV[:,:,ab_ind_b[1],ab_ind_b[0]] = -VVVV
temp[a:a+k] -= 0.5*lib.einsum('mldf,mled,aebf->ab',
t2_1_b, t2_1_b, eris_VVVV, optimize=True)
temp[a:a+k] += lib.einsum('mldf,mlde,aebf->ab',t2_1_ab,
t2_1_ab, eris_VVVV, optimize=True)
del eris_VVVV
a += k
M_ab_b += temp
a = 0
temp = np.zeros((nvir_a,nvir_a))
for dataset in eris.vVvV_p:
k = dataset.shape[0]
eris_vVvV = dataset[:].reshape(-1,nvir_b,nvir_a,nvir_b)
temp[a:a+k] -= 0.5*lib.einsum('mldf,mled,aebf->ab',
t2_1_b, t2_1_b, eris_vVvV, optimize=True)
temp[a:a+k] += lib.einsum('mldf,mlde,aebf->ab',t2_1_ab,
t2_1_ab, eris_vVvV, optimize=True)
a += k
M_ab_a += temp
elif eris.vvvv_p is None:
temp = np.zeros((nvir_b,nvir_b))
chnk_size = uadc_ao2mo.calculate_chunk_size(adc)
for a,b in lib.prange(0,nvir_b,chnk_size):
VVVV = dfadc.get_vvvv_antisym_df(adc, eris.LVV, a, chnk_size)
eris_VVVV = np.zeros((VVVV.shape[0],nvir_b,nvir_b,nvir_b))
eris_VVVV[:,:,ab_ind_b[0],ab_ind_b[1]] = VVVV
eris_VVVV[:,:,ab_ind_b[1],ab_ind_b[0]] = -VVVV
temp[a:b] -= 0.5*lib.einsum('mldf,mled,aebf->ab',
t2_1_b, t2_1_b, eris_VVVV, optimize=True)
temp[a:b] += lib.einsum('mldf,mlde,aebf->ab',t2_1_ab,
t2_1_ab, eris_VVVV, optimize=True)
del eris_VVVV
M_ab_b += temp
del temp
temp = np.zeros((nvir_a,nvir_a))
chnk_size = uadc_ao2mo.calculate_chunk_size(adc)
for a,b in lib.prange(0,nvir_a,chnk_size):
eris_vVvV = dfadc.get_vVvV_df(adc, eris.Lvv, eris.LVV, a, chnk_size)
temp[a:b] -= 0.5*lib.einsum('mldf,mled,aebf->ab',
t2_1_b, t2_1_b, eris_vVvV, optimize=True)
temp[a:b] += lib.einsum('mldf,mlde,aebf->ab',t2_1_ab,
t2_1_ab, eris_vVvV, optimize=True)
M_ab_a += temp
del temp
del t2_1_ab, t2_1_b
M_ab = (M_ab_a, M_ab_b)
cput0 = log.timer_debug1("Completed M_ab ADC(3) calculation", *cput0)
return M_ab
def get_diag(adc,M_ab=None,eris=None):
if adc.method not in ("adc(2)", "adc(2)-x", "adc(3)"):
raise NotImplementedError(adc.method)
if M_ab is None:
M_ab = adc.get_imds()
M_ab_a, M_ab_b = M_ab[0], M_ab[1]
nocc_a = adc.nocc_a
nocc_b = adc.nocc_b
nvir_a = adc.nvir_a
nvir_b = adc.nvir_b
n_singles_a = nvir_a
n_singles_b = nvir_b
n_doubles_aaa = nvir_a * (nvir_a - 1) * nocc_a // 2
n_doubles_bab = nocc_b * nvir_a * nvir_b
n_doubles_aba = nocc_a * nvir_b * nvir_a
n_doubles_bbb = nvir_b * (nvir_b - 1) * nocc_b // 2
dim = n_singles_a + n_singles_b + n_doubles_aaa + n_doubles_bab + n_doubles_aba + n_doubles_bbb
e_occ_a = adc.mo_energy_a[:nocc_a]
e_occ_b = adc.mo_energy_b[:nocc_b]
e_vir_a = adc.mo_energy_a[nocc_a:]
e_vir_b = adc.mo_energy_b[nocc_b:]
ab_ind_a = np.tril_indices(nvir_a, k=-1)
ab_ind_b = np.tril_indices(nvir_b, k=-1)
s_a = 0
f_a = n_singles_a
s_b = f_a
f_b = s_b + n_singles_b
s_aaa = f_b
f_aaa = s_aaa + n_doubles_aaa
s_bab = f_aaa
f_bab = s_bab + n_doubles_bab
s_aba = f_bab
f_aba = s_aba + n_doubles_aba
s_bbb = f_aba
f_bbb = s_bbb + n_doubles_bbb
d_i_a = e_occ_a[:,None]
d_ab_a = e_vir_a[:,None] + e_vir_a
D_n_a = -d_i_a + d_ab_a.reshape(-1)
D_n_a = D_n_a.reshape((nocc_a,nvir_a,nvir_a))
D_iab_a = D_n_a.copy()[:,ab_ind_a[0],ab_ind_a[1]].reshape(-1)
d_i_b = e_occ_b[:,None]
d_ab_b = e_vir_b[:,None] + e_vir_b
D_n_b = -d_i_b + d_ab_b.reshape(-1)
D_n_b = D_n_b.reshape((nocc_b,nvir_b,nvir_b))
D_iab_b = D_n_b.copy()[:,ab_ind_b[0],ab_ind_b[1]].reshape(-1)
d_ab_ab = e_vir_a[:,None] + e_vir_b
d_i_b = e_occ_b[:,None]
D_n_bab = -d_i_b + d_ab_ab.reshape(-1)
D_iab_bab = D_n_bab.reshape(-1)
d_ab_ab = e_vir_b[:,None] + e_vir_a
d_i_a = e_occ_a[:,None]
D_n_aba = -d_i_a + d_ab_ab.reshape(-1)
D_iab_aba = D_n_aba.reshape(-1)
diag = np.zeros(dim)
# Compute precond in p1-p1 block
M_ab_a_diag = np.diagonal(M_ab_a)
M_ab_b_diag = np.diagonal(M_ab_b)
diag[s_a:f_a] = M_ab_a_diag.copy()
diag[s_b:f_b] = M_ab_b_diag.copy()
# Compute precond in 2p1h-2p1h block
diag[s_aaa:f_aaa] = D_iab_a
diag[s_bab:f_bab] = D_iab_bab
diag[s_aba:f_aba] = D_iab_aba
diag[s_bbb:f_bbb] = D_iab_b
# ###### Additional terms for the preconditioner ####
# if (method == "adc(2)-x" or method == "adc(3)"):
#
# if eris is None:
# eris = adc.transform_integrals()
#
# if isinstance(eris.vvvv_p, np.ndarray):
#
# eris_oovv = eris.oovv
# eris_ovvo = eris.ovvo
# eris_OOVV = eris.OOVV
# eris_OVVO = eris.OVVO
# eris_OOvv = eris.OOvv
# eris_ooVV = eris.ooVV
#
# eris_vvvv = eris.vvvv_p
# temp = np.zeros((nocc_a, eris_vvvv.shape[0]))
# temp[:] += np.diag(eris_vvvv)
# diag[s_aaa:f_aaa] += temp.reshape(-1)
#
# eris_VVVV = eris.VVVV_p
# temp = np.zeros((nocc_b, eris_VVVV.shape[0]))
# temp[:] += np.diag(eris_VVVV)
# diag[s_bbb:f_bbb] += temp.reshape(-1)
#
# eris_vVvV = eris.vVvV_p
# temp = np.zeros((nocc_b, eris_vVvV.shape[0]))
# temp[:] += np.diag(eris_vVvV)
# diag[s_bab:f_bab] += temp.reshape(-1)
#
# temp = np.zeros((nocc_a, nvir_a, nvir_b))
# temp[:] += np.diag(eris_vVvV).reshape(nvir_a,nvir_b)
# temp = np.ascontiguousarray(temp.transpose(0,2,1))
# diag[s_aba:f_aba] += temp.reshape(-1)
#
# eris_ovov_p = np.ascontiguousarray(eris_oovv.transpose(0,2,1,3))
# eris_ovov_p -= np.ascontiguousarray(eris_ovvo.transpose(0,2,3,1))
# eris_ovov_p = eris_ovov_p.reshape(nocc_a*nvir_a, nocc_a*nvir_a)
#
# temp = np.zeros((eris_ovov_p.shape[0],nvir_a))
# temp.T[:] += np.diagonal(eris_ovov_p)
# temp = temp.reshape(nocc_a, nvir_a, nvir_a)
# diag[s_aaa:f_aaa] += -temp[:,ab_ind_a[0],ab_ind_a[1]].reshape(-1)
#
# temp = np.ascontiguousarray(temp.transpose(0,2,1))
# diag[s_aaa:f_aaa] += -temp[:,ab_ind_a[0],ab_ind_a[1]].reshape(-1)
#
# eris_OVOV_p = np.ascontiguousarray(eris_OOVV.transpose(0,2,1,3))
# eris_OVOV_p -= np.ascontiguousarray(eris_OVVO.transpose(0,2,3,1))
# eris_OVOV_p = eris_OVOV_p.reshape(nocc_b*nvir_b, nocc_b*nvir_b)
#
# temp = np.zeros((eris_OVOV_p.shape[0],nvir_b))
# temp.T[:] += np.diagonal(eris_OVOV_p)
# temp = temp.reshape(nocc_b, nvir_b, nvir_b)
# diag[s_bbb:f_bbb] += -temp[:,ab_ind_b[0],ab_ind_b[1]].reshape(-1)
#
# temp = np.ascontiguousarray(temp.transpose(0,2,1))
# diag[s_bbb:f_bbb] += -temp[:,ab_ind_b[0],ab_ind_b[1]].reshape(-1)
#
# temp = np.zeros((nvir_a, nocc_b, nvir_b))
# temp[:] += np.diagonal(eris_OVOV_p).reshape(nocc_b, nvir_b)
# temp = np.ascontiguousarray(temp.transpose(1,0,2))
# diag[s_bab:f_bab] += -temp.reshape(-1)
#
# temp = np.zeros((nvir_b, nocc_a, nvir_a))
# temp[:] += np.diagonal(eris_ovov_p).reshape(nocc_a, nvir_a)
# temp = np.ascontiguousarray(temp.transpose(1,0,2))
# diag[s_aba:f_aba] += -temp.reshape(-1)
#
# eris_OvOv_p = np.ascontiguousarray(eris_OOvv.transpose(0,2,1,3))
# eris_OvOv_p = eris_OvOv_p.reshape(nocc_b*nvir_a, nocc_b*nvir_a)
#
# temp = np.zeros((nvir_b, nocc_b, nvir_a))
# temp[:] += np.diagonal(eris_OvOv_p).reshape(nocc_b,nvir_a)
# temp = np.ascontiguousarray(temp.transpose(1,2,0))
# diag[s_bab:f_bab] += -temp.reshape(-1)
#
# eris_oVoV_p = np.ascontiguousarray(eris_ooVV.transpose(0,2,1,3))
# eris_oVoV_p = eris_oVoV_p.reshape(nocc_a*nvir_b, nocc_a*nvir_b)
#
# temp = np.zeros((nvir_a, nocc_a, nvir_b))
# temp[:] += np.diagonal(eris_oVoV_p).reshape(nocc_a,nvir_b)
# temp = np.ascontiguousarray(temp.transpose(1,2,0))
# diag[s_aba:f_aba] += -temp.reshape(-1)
# else:
# raise Exception("Precond not available for out-of-core and density-fitted algo")
return diag
def matvec(adc, M_ab=None, eris=None):
if adc.method not in ("adc(2)", "adc(2)-x", "adc(3)"):
raise NotImplementedError(adc.method)
method = adc.method
nocc_a = adc.nocc_a
nocc_b = adc.nocc_b
nvir_a = adc.nvir_a
nvir_b = adc.nvir_b
ab_ind_a = np.tril_indices(nvir_a, k=-1)
ab_ind_b = np.tril_indices(nvir_b, k=-1)
n_singles_a = nvir_a
n_singles_b = nvir_b
n_doubles_aaa = nvir_a * (nvir_a - 1) * nocc_a // 2
n_doubles_bab = nocc_b * nvir_a * nvir_b
n_doubles_aba = nocc_a * nvir_b * nvir_a
n_doubles_bbb = nvir_b * (nvir_b - 1) * nocc_b // 2
dim = n_singles_a + n_singles_b + n_doubles_aaa + n_doubles_bab + n_doubles_aba + n_doubles_bbb
e_occ_a = adc.mo_energy_a[:nocc_a]
e_occ_b = adc.mo_energy_b[:nocc_b]
e_vir_a = adc.mo_energy_a[nocc_a:]
e_vir_b = adc.mo_energy_b[nocc_b:]
if eris is None:
eris = adc.transform_integrals()
d_i_a = e_occ_a[:,None]
d_ab_a = e_vir_a[:,None] + e_vir_a
D_n_a = -d_i_a + d_ab_a.reshape(-1)
D_n_a = D_n_a.reshape((nocc_a,nvir_a,nvir_a))
D_iab_a = D_n_a.copy()[:,ab_ind_a[0],ab_ind_a[1]].reshape(-1)
d_i_b = e_occ_b[:,None]
d_ab_b = e_vir_b[:,None] + e_vir_b
D_n_b = -d_i_b + d_ab_b.reshape(-1)
D_n_b = D_n_b.reshape((nocc_b,nvir_b,nvir_b))
D_iab_b = D_n_b.copy()[:,ab_ind_b[0],ab_ind_b[1]].reshape(-1)
d_ab_ab = e_vir_a[:,None] + e_vir_b
d_i_b = e_occ_b[:,None]
D_n_bab = -d_i_b + d_ab_ab.reshape(-1)
D_iab_bab = D_n_bab.reshape(-1)
d_ab_ab = e_vir_b[:,None] + e_vir_a
d_i_a = e_occ_a[:,None]
D_n_aba = -d_i_a + d_ab_ab.reshape(-1)
D_iab_aba = D_n_aba.reshape(-1)
s_a = 0
f_a = n_singles_a
s_b = f_a
f_b = s_b + n_singles_b
s_aaa = f_b
f_aaa = s_aaa + n_doubles_aaa
s_bab = f_aaa
f_bab = s_bab + n_doubles_bab
s_aba = f_bab
f_aba = s_aba + n_doubles_aba
s_bbb = f_aba
f_bbb = s_bbb + n_doubles_bbb
if M_ab is None:
M_ab = adc.get_imds()
M_ab_a, M_ab_b = M_ab
#Calculate sigma vector
def sigma_(r):
cput0 = (logger.process_clock(), logger.perf_counter())
log = logger.Logger(adc.stdout, adc.verbose)
s = np.zeros(dim)
r_a = r[s_a:f_a]
r_b = r[s_b:f_b]
r_aaa = r[s_aaa:f_aaa]
r_bab = r[s_bab:f_bab]
r_aba = r[s_aba:f_aba]
r_bbb = r[s_bbb:f_bbb]
r_aaa_ = np.zeros((nocc_a, nvir_a, nvir_a))
r_aaa_[:, ab_ind_a[0], ab_ind_a[1]] = r_aaa.reshape(nocc_a, -1)
r_aaa_[:, ab_ind_a[1], ab_ind_a[0]] = -r_aaa.reshape(nocc_a, -1)
r_bbb_ = np.zeros((nocc_b, nvir_b, nvir_b))
r_bbb_[:, ab_ind_b[0], ab_ind_b[1]] = r_bbb.reshape(nocc_b, -1)
r_bbb_[:, ab_ind_b[1], ab_ind_b[0]] = -r_bbb.reshape(nocc_b, -1)
r_aba = r_aba.reshape(nocc_a,nvir_b,nvir_a)
r_bab = r_bab.reshape(nocc_b,nvir_a,nvir_b)
############ ADC(2) ab block ############################
s[s_a:f_a] = lib.einsum('ab,b->a',M_ab_a,r_a)
s[s_b:f_b] = lib.einsum('ab,b->a',M_ab_b,r_b)
############ ADC(2) a - ibc and ibc - a coupling blocks #########################
temp = np.zeros((nocc_a, nvir_a, nvir_a))
if eris.ovvv is None:
chnk_size = uadc_ao2mo.calculate_chunk_size(adc)
for a,b in lib.prange(0,nocc_a,chnk_size):
eris_ovvv = dfadc.get_ovvv_spin_df(
adc, eris.Lov, eris.Lvv, a, chnk_size).reshape(-1,nvir_a,nvir_a,nvir_a)
s[s_a:f_a] += 0.5*lib.einsum('icab,ibc->a',eris_ovvv, r_aaa_[a:b], optimize=True)
s[s_a:f_a] -= 0.5*lib.einsum('ibac,ibc->a',eris_ovvv, r_aaa_[a:b], optimize=True)
temp[a:b] += lib.einsum('icab,a->ibc', eris_ovvv, r_a, optimize=True)
temp[a:b] -= lib.einsum('ibac,a->ibc', eris_ovvv, r_a, optimize=True)
del eris_ovvv
else :
eris_ovvv = radc_ao2mo.unpack_eri_1(eris.ovvv, nvir_a)
s[s_a:f_a] += 0.5*lib.einsum('icab,ibc->a',eris_ovvv, r_aaa_, optimize=True)
s[s_a:f_a] -= 0.5*lib.einsum('ibac,ibc->a',eris_ovvv, r_aaa_, optimize=True)
temp += lib.einsum('icab,a->ibc', eris_ovvv, r_a, optimize=True)
temp -= lib.einsum('ibac,a->ibc', eris_ovvv, r_a, optimize=True)
del eris_ovvv
s[s_aaa:f_aaa] += temp[:,ab_ind_a[0],ab_ind_a[1]].reshape(-1)
del temp
temp = np.zeros((nocc_b, nvir_a, nvir_b))
if eris.OVvv is None:
chnk_size = uadc_ao2mo.calculate_chunk_size(adc)
for a,b in lib.prange(0,nocc_b,chnk_size):
eris_OVvv = dfadc.get_ovvv_spin_df(
adc, eris.LOV, eris.Lvv, a, chnk_size).reshape(-1,nvir_b,nvir_a,nvir_a)
s[s_a:f_a] += lib.einsum('icab,ibc->a', eris_OVvv, r_bab[a:b], optimize=True)
temp[a:b] += lib.einsum('icab,a->ibc', eris_OVvv, r_a, optimize=True)
del eris_OVvv
else :
eris_OVvv = radc_ao2mo.unpack_eri_1(eris.OVvv, nvir_a)
s[s_a:f_a] += lib.einsum('icab,ibc->a', eris_OVvv, r_bab, optimize=True)
temp += lib.einsum('icab,a->ibc', eris_OVvv, r_a, optimize=True)
del eris_OVvv
s[s_bab:f_bab] += temp.reshape(-1)
del temp
temp = np.zeros((nocc_b, nvir_b, nvir_b))
if eris.OVVV is None:
chnk_size = uadc_ao2mo.calculate_chunk_size(adc)
for a,b in lib.prange(0,nocc_b,chnk_size):
eris_OVVV = dfadc.get_ovvv_spin_df(
adc, eris.LOV, eris.LVV, a, chnk_size).reshape(-1,nvir_b,nvir_b,nvir_b)
s[s_b:f_b] += 0.5*lib.einsum('icab,ibc->a',eris_OVVV, r_bbb_[a:b], optimize=True)
s[s_b:f_b] -= 0.5*lib.einsum('ibac,ibc->a',eris_OVVV, r_bbb_[a:b], optimize=True)
temp[a:b] += lib.einsum('icab,a->ibc', eris_OVVV, r_b, optimize=True)
temp[a:b] -= lib.einsum('ibac,a->ibc', eris_OVVV, r_b, optimize=True)
del eris_OVVV
else :
eris_OVVV = radc_ao2mo.unpack_eri_1(eris.OVVV, nvir_b)
s[s_b:f_b] += 0.5*lib.einsum('icab,ibc->a',eris_OVVV, r_bbb_, optimize=True)
s[s_b:f_b] -= 0.5*lib.einsum('ibac,ibc->a',eris_OVVV, r_bbb_, optimize=True)
temp += lib.einsum('icab,a->ibc', eris_OVVV, r_b, optimize=True)
temp -= lib.einsum('ibac,a->ibc', eris_OVVV, r_b, optimize=True)
del eris_OVVV
s[s_bbb:f_bbb] += temp[:,ab_ind_b[0],ab_ind_b[1]].reshape(-1)
del temp
temp = np.zeros((nocc_a, nvir_b, nvir_a))
if eris.ovVV is None:
chnk_size = uadc_ao2mo.calculate_chunk_size(adc)
for a,b in lib.prange(0,nocc_a,chnk_size):
eris_ovVV = dfadc.get_ovvv_spin_df(
adc, eris.Lov, eris.LVV, a, chnk_size).reshape(-1,nvir_a,nvir_b,nvir_b)
s[s_b:f_b] += lib.einsum('icab,ibc->a', eris_ovVV, r_aba[a:b], optimize=True)
temp[a:b] += lib.einsum('icab,a->ibc', eris_ovVV, r_b, optimize=True)
del eris_ovVV
else :
eris_ovVV = radc_ao2mo.unpack_eri_1(eris.ovVV, nvir_b)
s[s_b:f_b] += lib.einsum('icab,ibc->a', eris_ovVV, r_aba, optimize=True)
temp += lib.einsum('icab,a->ibc', eris_ovVV, r_b, optimize=True)
del eris_ovVV
s[s_aba:f_aba] += temp.reshape(-1)
del temp
############### ADC(2) iab - jcd block ############################
s[s_aaa:f_aaa] += D_iab_a * r_aaa
s[s_bab:f_bab] += D_iab_bab * r_bab.reshape(-1)
s[s_aba:f_aba] += D_iab_aba * r_aba.reshape(-1)
s[s_bbb:f_bbb] += D_iab_b * r_bbb
############### ADC(3) iab - jcd block ############################
if (method == "adc(2)-x" or method == "adc(3)"):
eris_oovv = eris.oovv
eris_OOVV = eris.OOVV
eris_ooVV = eris.ooVV
eris_OOvv = eris.OOvv
eris_ovvo = eris.ovvo
eris_OVVO = eris.OVVO
eris_ovVO = eris.ovVO
eris_OVvo = eris.OVvo
r_aaa = r_aaa.reshape(nocc_a,-1)
r_bbb = r_bbb.reshape(nocc_b,-1)
r_aaa_u = np.zeros((nocc_a,nvir_a,nvir_a))
r_aaa_u[:,ab_ind_a[0],ab_ind_a[1]]= r_aaa.copy()
r_aaa_u[:,ab_ind_a[1],ab_ind_a[0]]= -r_aaa.copy()
r_bbb_u = None
r_bbb_u = np.zeros((nocc_b,nvir_b,nvir_b))
r_bbb_u[:,ab_ind_b[0],ab_ind_b[1]]= r_bbb.copy()
r_bbb_u[:,ab_ind_b[1],ab_ind_b[0]]= -r_bbb.copy()
if isinstance(eris.vvvv_p, np.ndarray):
eris_vvvv = eris.vvvv_p
temp_1 = np.dot(r_aaa,eris_vvvv.T)
del eris_vvvv
elif isinstance(eris.vvvv_p, list):
temp_1 = contract_r_vvvv_antisym(adc,r_aaa_u,eris.vvvv_p)
temp_1 = temp_1[:,ab_ind_a[0],ab_ind_a[1]]
else:
temp_1 = contract_r_vvvv_antisym(adc,r_aaa_u,eris.Lvv)
temp_1 = temp_1[:,ab_ind_a[0],ab_ind_a[1]]
s[s_aaa:f_aaa] += temp_1.reshape(-1)
if isinstance(eris.VVVV_p, np.ndarray):
eris_VVVV = eris.VVVV_p
temp_1 = np.dot(r_bbb,eris_VVVV.T)
del eris_VVVV
elif isinstance(eris.VVVV_p, list):
temp_1 = contract_r_vvvv_antisym(adc,r_bbb_u,eris.VVVV_p)
temp_1 = temp_1[:,ab_ind_b[0],ab_ind_b[1]]
else:
temp_1 = contract_r_vvvv_antisym(adc,r_bbb_u,eris.LVV)
temp_1 = temp_1[:,ab_ind_b[0],ab_ind_b[1]]
s[s_bbb:f_bbb] += temp_1.reshape(-1)
if isinstance(eris.vVvV_p, np.ndarray):
r_bab_t = r_bab.reshape(nocc_b,-1)
r_aba_t = r_aba.transpose(0,2,1).reshape(nocc_a,-1)
eris_vVvV = eris.vVvV_p
s[s_bab:f_bab] += np.dot(r_bab_t,eris_vVvV.T).reshape(-1)
temp_1 = np.dot(r_aba_t,eris_vVvV.T).reshape(nocc_a, nvir_a,nvir_b)
s[s_aba:f_aba] += temp_1.transpose(0,2,1).copy().reshape(-1)
elif isinstance(eris.vVvV_p, list):
temp_1 = contract_r_vvvv(adc,r_bab,eris.vVvV_p)
temp_2 = contract_r_vvvv(adc,r_aba,eris.VvVv_p)
s[s_bab:f_bab] += temp_1.reshape(-1)
s[s_aba:f_aba] += temp_2.reshape(-1)
else:
temp_1 = contract_r_vvvv(adc,r_bab,(eris.Lvv,eris.LVV))
temp_2 = contract_r_vvvv(adc,r_aba,(eris.LVV,eris.Lvv))
s[s_bab:f_bab] += temp_1.reshape(-1)
s[s_aba:f_aba] += temp_2.reshape(-1)
temp = 0.5*lib.einsum('jiyz,jzx->ixy',eris_oovv,r_aaa_u,optimize=True)
temp -= 0.5*lib.einsum('jzyi,jzx->ixy',eris_ovvo,r_aaa_u,optimize=True)
temp +=0.5*lib.einsum('jzyi,jxz->ixy',eris_OVvo,r_bab,optimize=True)
s[s_aaa:f_aaa] += temp[:,ab_ind_a[0],ab_ind_a[1]].reshape(-1)
s[s_bab:f_bab] -= 0.5*lib.einsum('jzyi,jzx->ixy',eris_ovVO,
r_aaa_u,optimize=True).reshape(-1)
s[s_bab:f_bab] -= 0.5*lib.einsum('jiyz,jxz->ixy',eris_OOVV,
r_bab,optimize=True).reshape(-1)
s[s_bab:f_bab] += 0.5*lib.einsum('jzyi,jxz->ixy',eris_OVVO,
r_bab,optimize=True).reshape(-1)
temp = 0.5*lib.einsum('jiyz,jzx->ixy',eris_OOVV,r_bbb_u,optimize=True)
temp -= 0.5*lib.einsum('jzyi,jzx->ixy',eris_OVVO,r_bbb_u,optimize=True)
temp +=0.5* lib.einsum('jzyi,jxz->ixy',eris_ovVO,r_aba,optimize=True)
s[s_bbb:f_bbb] += temp[:,ab_ind_b[0],ab_ind_b[1]].reshape(-1)
s[s_aba:f_aba] -= 0.5*lib.einsum('jiyz,jxz->ixy',eris_oovv,
r_aba,optimize=True).reshape(-1)
s[s_aba:f_aba] += 0.5*lib.einsum('jzyi,jxz->ixy',eris_ovvo,
r_aba,optimize=True).reshape(-1)
s[s_aba:f_aba] -= 0.5*lib.einsum('jzyi,jzx->ixy',eris_OVvo,
r_bbb_u,optimize=True).reshape(-1)
temp = -0.5*lib.einsum('jixz,jzy->ixy',eris_oovv,r_aaa_u,optimize=True)
temp += 0.5*lib.einsum('jzxi,jzy->ixy',eris_ovvo,r_aaa_u,optimize=True)
temp -= 0.5*lib.einsum('jzxi,jyz->ixy',eris_OVvo,r_bab,optimize=True)
s[s_aaa:f_aaa] += temp[:,ab_ind_a[0],ab_ind_a[1]].reshape(-1)
s[s_bab:f_bab] -= 0.5*lib.einsum('jixz,jzy->ixy',
eris_OOvv,r_bab,optimize=True).reshape(-1)
temp = -0.5*lib.einsum('jixz,jzy->ixy',eris_OOVV,r_bbb_u,optimize=True)
temp += 0.5*lib.einsum('jzxi,jzy->ixy',eris_OVVO,r_bbb_u,optimize=True)
temp -= 0.5*lib.einsum('jzxi,jyz->ixy',eris_ovVO,r_aba,optimize=True)
s[s_bbb:f_bbb] += temp[:,ab_ind_b[0],ab_ind_b[1]].reshape(-1)
s[s_aba:f_aba] -= 0.5*lib.einsum('jixz,jzy->ixy',eris_ooVV,
r_aba,optimize=True).reshape(-1)
temp = 0.5*lib.einsum('jixw,jyw->ixy',eris_oovv,r_aaa_u,optimize=True)
temp -= 0.5*lib.einsum('jwxi,jyw->ixy',eris_ovvo,r_aaa_u,optimize=True)
temp -= 0.5*lib.einsum('jwxi,jyw->ixy',eris_OVvo,r_bab,optimize=True)
s[s_aaa:f_aaa] += temp[:,ab_ind_a[0],ab_ind_a[1]].reshape(-1)
s[s_bab:f_bab] -= 0.5*lib.einsum('jixw,jwy->ixy',eris_OOvv,
r_bab,optimize=True).reshape(-1)
temp = 0.5*lib.einsum('jixw,jyw->ixy',eris_OOVV,r_bbb_u,optimize=True)
temp -= 0.5*lib.einsum('jwxi,jyw->ixy',eris_OVVO,r_bbb_u,optimize=True)
temp -= 0.5*lib.einsum('jwxi,jyw->ixy',eris_ovVO,r_aba,optimize=True)
s[s_bbb:f_bbb] += temp[:,ab_ind_b[0],ab_ind_b[1]].reshape(-1)
s[s_aba:f_aba] -= 0.5*lib.einsum('jixw,jwy->ixy',eris_ooVV,
r_aba,optimize=True).reshape(-1)
temp = -0.5*lib.einsum('jiyw,jxw->ixy',eris_oovv,r_aaa_u,optimize=True)
temp += 0.5*lib.einsum('jwyi,jxw->ixy',eris_ovvo,r_aaa_u,optimize=True)
temp += 0.5*lib.einsum('jwyi,jxw->ixy',eris_OVvo,r_bab,optimize=True)
s[s_aaa:f_aaa] += temp[:,ab_ind_a[0],ab_ind_a[1]].reshape(-1)
s[s_bab:f_bab] -= 0.5*lib.einsum('jiyw,jxw->ixy',eris_OOVV,
r_bab,optimize=True).reshape(-1)
s[s_bab:f_bab] += 0.5*lib.einsum('jwyi,jxw->ixy',eris_OVVO,
r_bab,optimize=True).reshape(-1)
s[s_bab:f_bab] += 0.5*lib.einsum('jwyi,jxw->ixy',eris_ovVO,
r_aaa_u,optimize=True).reshape(-1)
s[s_aba:f_aba] -= 0.5*lib.einsum('jiyw,jxw->ixy',eris_oovv,
r_aba,optimize=True).reshape(-1)
s[s_aba:f_aba] += 0.5*lib.einsum('jwyi,jxw->ixy',eris_ovvo,
r_aba,optimize=True).reshape(-1)
s[s_aba:f_aba] += 0.5*lib.einsum('jwyi,jxw->ixy',eris_OVvo,
r_bbb_u,optimize=True).reshape(-1)
temp = -0.5*lib.einsum('jiyw,jxw->ixy',eris_OOVV,r_bbb_u,optimize=True)
temp += 0.5*lib.einsum('jwyi,jxw->ixy',eris_OVVO,r_bbb_u,optimize=True)
temp += 0.5*lib.einsum('jwyi,jxw->ixy',eris_ovVO,r_aba,optimize=True)
s[s_bbb:f_bbb] += temp[:,ab_ind_b[0],ab_ind_b[1]].reshape(-1)
if (method == "adc(3)"):
eris_ovoo = eris.ovoo
eris_OVOO = eris.OVOO
eris_ovOO = eris.ovOO
eris_OVoo = eris.OVoo
############### ADC(3) a - ibc block and ibc-a coupling blocks ########################
t2_1_a = adc.t2[0][0][:]
t2_1_ab = adc.t2[0][1][:]
t2_1_a_t = t2_1_a[:,:,ab_ind_a[0],ab_ind_a[1]]
r_aaa = r_aaa.reshape(nocc_a,-1)
temp = 0.5*lib.einsum('lmp,jp->lmj',t2_1_a_t,r_aaa)
del t2_1_a_t
s[s_a:f_a] += lib.einsum('lmj,lamj->a',temp, eris_ovoo, optimize=True)
s[s_a:f_a] -= lib.einsum('lmj,malj->a',temp, eris_ovoo, optimize=True)
del temp