def test_n3_diffuse_Ta(self):
nk = (1, 1, 2)
ehf_bench = -6.1870676561720721
ecc_bench = -0.06764836939412185
cc = pbcc.kccsd_rhf.RCCSD(kmf)
cc.conv_tol = 1e-8
eris = cc.ao2mo()
eris.mo_energy = [
eris.fock[ikpt].diagonal() for ikpt in range(cc.nkpts)
]
ecc, t1, t2 = cc.kernel(eris=eris)
ehf = kmf.e_tot
self.assertAlmostEqual(ehf, ehf_bench, 6)
self.assertAlmostEqual(ecc, ecc_bench, 6)
eom = EOMIP_Ta(cc)
e, v = eom.ipccsd(nroots=2, koopmans=True, kptlist=(0, ), eris=eris)
self.assertAlmostEqual(e[0][0], -1.146351230068405, 6)
self.assertAlmostEqual(e[0][1], -1.10725570884212, 6)
eom = EOMEA_Ta(cc)
e, v = eom.eaccsd(nroots=2, koopmans=True, kptlist=[0], eris=eris)
self.assertAlmostEqual(e[0][0], 1.267728933294929, 6)
self.assertAlmostEqual(e[0][1], 1.280954973687476, 6)
eom = EOMEA_Ta(cc)
e, v = eom.eaccsd(nroots=2, koopmans=True, kptlist=[1], eris=eris)
self.assertAlmostEqual(e[0][0], 1.229047959680129, 6)
self.assertAlmostEqual(e[0][1], 1.384154370672317, 6)
def test_n3_diffuse_Ta_against_so(self):
ehf_bench = -6.1870676561720721
ecc_bench = -0.06764836939412185
cc = pbcc.kccsd_rhf.RCCSD(kmf)
cc.conv_tol = 1e-10
eris = cc.ao2mo()
eris.mo_energy = [
eris.fock[ikpt].diagonal() for ikpt in range(cc.nkpts)
]
ecc, t1, t2 = cc.kernel(eris=eris)
ehf = kmf.e_tot
self.assertAlmostEqual(ehf, ehf_bench, 6)
self.assertAlmostEqual(ecc, ecc_bench, 6)
eom = EOMEA_Ta(cc)
eea_rccsd = eom.eaccsd_star(nroots=1,
koopmans=True,
kptlist=(0, ),
eris=eris)
eom = EOMIP_Ta(cc)
eip_rccsd = eom.ipccsd_star(nroots=1,
koopmans=True,
kptlist=(0, ),
eris=eris)
self.assertAlmostEqual(eea_rccsd[0][0], 1.2610123166324307, 6)
self.assertAlmostEqual(eip_rccsd[0][0], -1.1435100754903331, 6)
from pyscf.pbc.cc import kccsd
cc = pbcc.KGCCSD(kmf)
cc.conv_tol = 1e-10
eris = cc.ao2mo()
eris.mo_energy = [
eris.fock[ikpt].diagonal() for ikpt in range(cc.nkpts)
]
ecc, t1, t2 = cc.kernel(eris=eris)
ehf = kmf.e_tot
self.assertAlmostEqual(ehf, ehf_bench, 6)
self.assertAlmostEqual(ecc, ecc_bench, 6)
from pyscf.pbc.cc import eom_kccsd_ghf
eom = eom_kccsd_ghf.EOMEA_Ta(cc)
eea_gccsd = eom.eaccsd_star(nroots=1,
koopmans=True,
kptlist=(0, ),
eris=eris)
eom = eom_kccsd_ghf.EOMIP_Ta(cc)
eip_gccsd = eom.ipccsd_star(nroots=1,
koopmans=True,
kptlist=(0, ),
eris=eris)
self.assertAlmostEqual(eea_gccsd[0][0], 1.2610123166324307, 6)
self.assertAlmostEqual(eip_gccsd[0][0], -1.1435100754903331, 6)
# Usually slightly higher agreement when comparing directly against one another
self.assertAlmostEqual(eea_gccsd[0][0], eea_rccsd[0][0], 9)
self.assertAlmostEqual(eip_gccsd[0][0], eip_rccsd[0][0], 9)
kmf = pbchf.KRHF(cell, kpts, exxdiv=None)#, conv_tol=1e-10) kpoint_energy = kmf.kernel() # Perform our ground state ccsd calculation mykcc = pbccc.KRCCSD(kmf) eris = mykcc.ao2mo() kccsd_energy = mykcc.ccsd(eris=eris)[0] ekcc = mykcc.ecc # To run an EOM-CCSD(T)*a calculation, you need to use the EOMIP_Ta/ # /EOMEA_Ta classes that will add in the contribution of T3[2] to # T1/T2 as well as any other relevant EOM-CCSD intermediates. myeom = EOMIP_Ta(mykcc) # We then call the ip-ccsd* function that will find both the right # and left eigenvectors of EOM-CCSD (with perturbed intermediates) # and run EOM-CCSD* myeom.ipccsd_star(nroots=2, kptlist=[0], eris=eris) # If we need to run both an IP and EA calculation, the t3[2] intermediates # would need to be created two times. Because creating the t3[2] intermediates # is fairly expensive, we can reduce the computational cost by creating # the intermediates directly and passing them in. from pyscf.pbc.cc import eom_kccsd_rhf imds = eom_kccsd_rhf._IMDS(mykcc, eris=eris) imds = imds.make_t3p2_ip_ea(mykcc) # Now call EOMIP_Ta/EOMEA_Ta directly using these intermediates myeom = EOMIP_Ta(mykcc) myeom.ipccsd_star(nroots=2, kptlist=[0], imds=imds) myeom = EOMEA_Ta(mykcc) myeom.eaccsd_star(nroots=2, kptlist=[0], imds=imds)