示例#1
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def run_ccsd(hf_chkfile, chkfile):
    mol, mf = pyqmc.recover_pyscf(hf_chkfile)
    mycc = pyscf.cc.CCSD(mf).run(verbose=0)
    dm1 = mycc.make_rdm1()
    from pyscf.cc import ccsd_t_lambda_slow as ccsd_t_lambda
    from pyscf.cc import ccsd_t_rdm_slow as ccsd_t_rdm
    eris = mycc.ao2mo()
    conv, l1, l2 = ccsd_t_lambda.kernel(mycc, eris, mycc.t1, mycc.t2)
    dm1_t = ccsd_t_rdm.make_rdm1(mycc, mycc.t1, mycc.t2, l1, l2, eris=eris)
    pyscf.lib.chkfile.save(chkfile, 'ccsd', {'energy': mycc.e_tot, 'rdm': dm1})
    pyscf.lib.chkfile.save(chkfile, 'ccsdt', {
        'energy': mycc.ccsd_t(),
        'rdm': dm1_t
    })
示例#2
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                [1, (0.2, .757, .487)]]
    mol.basis = '631g'
    mol.build()
    mf0 = mf = scf.RHF(mol).run(conv_tol=1.)
    mf = scf.addons.convert_to_uhf(mf)

    from pyscf.cc import ccsd_t_lambda_slow as ccsd_t_lambda
    from pyscf.cc import ccsd_t_rdm_slow as ccsd_t_rdm
    mycc0 = cc.CCSD(mf0)
    eris0 = mycc0.ao2mo()
    mycc0.kernel(eris=eris0)
    t1 = mycc0.t1
    t2 = mycc0.t2
    imds = ccsd_t_lambda.make_intermediates(mycc0, t1, t2, eris0)
    l1, l2 = ccsd_t_lambda.update_lambda(mycc0, t1, t2, t1, t2, eris0, imds)
    dm1ref = ccsd_t_rdm.make_rdm1(mycc0, t1, t2, l1, l2, eris0)
    dm2ref = ccsd_t_rdm.make_rdm2(mycc0, t1, t2, l1, l2, eris0)

    t1 = (t1, t1)
    t2aa = t2 - t2.transpose(1, 0, 2, 3)
    t2 = (t2aa, t2, t2aa)
    l1 = (l1, l1)
    l2aa = l2 - l2.transpose(1, 0, 2, 3)
    l2 = (l2aa, l2, l2aa)
    mycc = cc.UCCSD(mf)
    eris = mycc.ao2mo()
    dm1 = make_rdm1(mycc, t1, t2, l1, l2, eris)
    dm2 = make_rdm2(mycc, t1, t2, l1, l2, eris)
    trdm1 = dm1[0] + dm1[1]
    trdm2 = dm2[0] + dm2[1] + dm2[1].transpose(2, 3, 0, 1) + dm2[2]
    print(abs(trdm1 - dm1ref).max())
示例#3
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#
mo_vir = cv
coeff = numpy.hstack([mo_core, mo_occ, mo_vir])
nao, nmo = coeff.shape
nocc = mol.nelectron // 2
occ = numpy.zeros(nmo)
for i in range(nocc):
    occ[i] = 2.0
#
mycc = cc.CCSD(mf, mo_coeff=coeff, mo_occ=occ)
mycc.diis_space = 10
mycc.frozen = ncore
mycc.conv_tol = 1e-6
mycc.conv_tol_normt = 1e-6
mycc.max_cycle = 150
ecc, t1, t2 = mycc.kernel()
nao, nmo = coeff.shape
eris = mycc.ao2mo()
e3 = ccsd_t.kernel(mycc, eris, t1, t2)
lib.logger.info(mycc, "* CCSD(T) energy : %12.6f" % (ehf + ecc + e3))
l1, l2 = ccsd_t_lambda.kernel(mycc, eris, t1, t2)[1:]
rdm1 = ccsd_t_rdm.make_rdm1(mycc, t1, t2, l1, l2, eris=eris)
rdm2 = ccsd_t_rdm.make_rdm2(mycc, t1, t2, l1, l2, eris=eris)
#
eri_mo = ao2mo.kernel(mf._eri, coeff[:, :nmo], compact=False)
eri_mo = eri_mo.reshape(nmo, nmo, nmo, nmo)
h1 = reduce(numpy.dot, (coeff[:, :nmo].T, mf.get_hcore(), coeff[:, :nmo]))
ecc = (numpy.einsum('ij,ji->', h1, rdm1) +
       numpy.einsum('ijkl,ijkl->', eri_mo, rdm2) * .5 + mf.mol.energy_nuc())
lib.logger.info(mycc, "* Energy with 1/2-RDM : %.8f" % ecc)
示例#4
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        [1 , (0.2,  .757 , .487)]]
    mol.basis = '631g'
    mol.build()
    mf0 = mf = scf.RHF(mol).run(conv_tol=1.)
    mf = scf.addons.convert_to_uhf(mf)

    from pyscf.cc import ccsd_t_lambda_slow as ccsd_t_lambda
    from pyscf.cc import ccsd_t_rdm_slow as ccsd_t_rdm
    mycc0 = cc.CCSD(mf0)
    eris0 = mycc0.ao2mo()
    mycc0.kernel(eris=eris0)
    t1 = mycc0.t1
    t2 = mycc0.t2
    imds = ccsd_t_lambda.make_intermediates(mycc0, t1, t2, eris0)
    l1, l2 = ccsd_t_lambda.update_lambda(mycc0, t1, t2, t1, t2, eris0, imds)
    dm1ref = ccsd_t_rdm.make_rdm1(mycc0, t1, t2, l1, l2, eris0)
    dm2ref = ccsd_t_rdm.make_rdm2(mycc0, t1, t2, l1, l2, eris0)

    t1 = (t1, t1)
    t2aa = t2 - t2.transpose(1,0,2,3)
    t2 = (t2aa, t2, t2aa)
    l1 = (l1, l1)
    l2aa = l2 - l2.transpose(1,0,2,3)
    l2 = (l2aa, l2, l2aa)
    mycc = cc.UCCSD(mf)
    eris = mycc.ao2mo()
    dm1 = make_rdm1(mycc, t1, t2, l1, l2, eris)
    dm2 = make_rdm2(mycc, t1, t2, l1, l2, eris)
    trdm1 = dm1[0] + dm1[1]
    trdm2 = dm2[0] + dm2[1] + dm2[1].transpose(2,3,0,1) + dm2[2]
    print(abs(trdm1 - dm1ref).max())
示例#5
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def solve(mol, nel, cf_core, cf_gs, ImpOrbs, chempot=0., n_orth=0):
    # cf_core : core orbitals (in AO basis, assumed orthonormal)
    # cf_gs   : guess orbitals (in AO basis)
    # ImpOrbs : cf_gs -> impurity orbitals transformation
    # n_orth  : number of orthonormal orbitals in cf_gs [1..n_orth]

    mol_ = gto.Mole()
    mol_.build(verbose=0)
    mol_.nelectron = nel
    mol_.incore_anyway = True

    cfx = cf_gs
    Sf = mol.intor_symmetric('cint1e_ovlp_sph')
    Hc  = mol.intor_symmetric('cint1e_kin_sph') \
        + mol.intor_symmetric('cint1e_nuc_sph')

    occ = np.zeros((cfx.shape[1], ))
    occ[:nel / 2] = 2.

    # core contributions
    dm_core = np.dot(cf_core, cf_core.T) * 2
    jk_core = scf.hf.get_veff(mol, dm_core)
    e_core  =     np.trace(np.dot(Hc, dm_core)) \
            + 0.5*np.trace(np.dot(jk_core, dm_core))

    # transform integrals
    Sp = np.dot(cfx.T, np.dot(Sf, cfx))
    Hp = np.dot(cfx.T, np.dot(Hc, cfx))
    jkp = np.dot(cfx.T, np.dot(jk_core, cfx))
    intsp = ao2mo.outcore.full_iofree(mol, cfx)

    # orthogonalize cf [virtuals]
    cf = np.zeros((cfx.shape[1], ) * 2, )
    if n_orth > 0:
        assert (n_orth <= cfx.shape[1])
        assert (np.allclose(np.eye(n_orth), Sp[:n_orth, :n_orth]))
    else:
        n_orth = 0

    cf[:n_orth, :n_orth] = np.eye(n_orth)
    if n_orth < cfx.shape[1]:
        val, vec = sla.eigh(-Sp[n_orth:, n_orth:])
        idx = -val > 1.e-12
        U = np.dot(vec[:,idx]*1./(np.sqrt(-val[idx])), \
                   vec[:,idx].T)
        cf[n_orth:, n_orth:] = U

    # define ImpOrbs projection
    Xp = np.dot(ImpOrbs, ImpOrbs.T)

    # Si = np.dot(ImpOrbs.T, np.dot(Sp, ImpOrbs))
    # Mp = np.dot(ImpOrbs, np.dot(sla.inv(Si), ImpOrbs.T))
    Np = np.dot(Sp, Xp)
    # print ( np.allclose(Np, np.dot(Np, np.dot(Mp, Np))) )

    # HF calculation
    mol_.energy_nuc = lambda *args: mol.energy_nuc() + e_core
    mf = scf.RHF(mol_)
    #mf.verbose = 4
    mf.mo_coeff = cf
    mf.mo_occ = occ
    mf.get_ovlp = lambda *args: Sp
    mf.get_hcore = lambda *args: Hp + jkp - 0.5 * chempot * (Np + Np.T)
    mf._eri = ao2mo.restore(8, intsp, cfx.shape[1])

    nt = scf.newton(mf)
    #nt.verbose = 4
    nt.max_cycle_inner = 1
    nt.max_stepsize = 0.25
    nt.ah_max_cycle = 32
    nt.ah_start_tol = 1.0e-12
    nt.ah_grad_trust_region = 1.0e8
    nt.conv_tol_grad = 1.0e-6

    nt.kernel()
    cf = nt.mo_coeff
    if not nt.converged:
        raise RuntimeError('hf failed to converge')
    mf.mo_coeff = nt.mo_coeff
    mf.mo_energy = nt.mo_energy
    mf.mo_occ = nt.mo_occ

    #CCSD(T) only implementation available is slow.
    from pyscf.cc import ccsd_t_slow as ccsd_t
    from pyscf.cc import ccsd_t_lambda_slow as ccsd_t_lambda
    from pyscf.cc import ccsd_t_rdm_slow as ccsd_t_rdm

    # CC solution
    ccsolver = cc.CCSD(mf)
    ccsolver.verbose = 5
    ecc, t1, t2 = ccsolver.kernel()
    # CCSD(T) solution
    eris = ccsolver.ao2mo()
    e3ref = ccsd_t.kernel(ccsolver, eris, t1, t2)
    l1, l2 = ccsd_t_lambda.kernel(ccsolver, eris, t1, t2)[1:]
    print("CCSD(T) energy ", ecc + e3ref)

    rdm1 = ccsd_t_rdm.make_rdm1(ccsolver, t1, t2, l1, l2, eris=eris)
    rdm2 = ccsd_t_rdm.make_rdm2(ccsolver, t1, t2, l1, l2, eris=eris)

    # transform rdm's to original basis
    tei = ao2mo.restore(1, intsp, cfx.shape[1])
    rdm1 = np.dot(cf, np.dot(rdm1, cf.T))
    rdm2 = np.einsum('ai,ijkl->ajkl', cf, rdm2)
    rdm2 = np.einsum('bj,ajkl->abkl', cf, rdm2)
    rdm2 = np.einsum('ck,abkl->abcl', cf, rdm2)
    rdm2 = np.einsum('dl,abcl->abcd', cf, rdm2)

    ImpEnergy = +0.25 *np.einsum('ij,jk,ki->', 2*Hp+jkp, rdm1, Xp) \
                +0.25 *np.einsum('ij,jk,ki->', 2*Hp+jkp, Xp, rdm1) \
                +0.125*np.einsum('ijkl,ijkm,ml->', tei, rdm2, Xp) \
                +0.125*np.einsum('ijkl,ijml,mk->', tei, rdm2, Xp) \
                +0.125*np.einsum('ijkl,imkl,mj->', tei, rdm2, Xp) \
                +0.125*np.einsum('ijkl,mjkl,mi->', tei, rdm2, Xp)

    Nel = np.trace(np.dot(np.dot(rdm1, Sp), Xp))

    return Nel, ImpEnergy
示例#6
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# CCSD energy based on density matrices
#
h1 = numpy.einsum('pi,pq,qj->ij', mf.mo_coeff.conj(), mf.get_hcore(),
                  mf.mo_coeff)
nmo = mf.mo_coeff.shape[1]
eri = ao2mo.kernel(mol, mf.mo_coeff, compact=False).reshape([nmo] * 4)
E = numpy.einsum('pq,qp', h1, dm1)
# Note dm2 is transposed to simplify its contraction to integrals
E += numpy.einsum('pqrs,pqrs', eri, dm2) * .5
E += mol.energy_nuc()
print('E(CCSD) = %s, reference %s' % (E, mycc.e_tot))

# When plotting CCSD density on grids, CCSD density matrices need to be
# transformed to AO basis representation.
dm1_ao = numpy.einsum('pi,ij,qj->pq', mf.mo_coeff, dm1, mf.mo_coeff.conj())

from pyscf.tools import cubegen
cubegen.density(mol, 'rho_ccsd.cube', dm1_ao)

###
#
# Compute CCSD(T) density matrices with ccsd_t-slow implementation
# (as of pyscf v1.7)
#
from pyscf.cc import ccsd_t_lambda_slow as ccsd_t_lambda
from pyscf.cc import ccsd_t_rdm_slow as ccsd_t_rdm
eris = mycc.ao2mo()
conv, l1, l2 = ccsd_t_lambda.kernel(mycc, eris, mycc.t1, mycc.t2)
dm1 = ccsd_t_rdm.make_rdm1(mycc, mycc.t1, mycc.t2, l1, l2, eris=eris)
dm2 = ccsd_t_rdm.make_rdm2(mycc, mycc.t1, mycc.t2, l1, l2, eris=eris)