Exemplo n.º 1
0
def test_first_hyperpolarizability_or_rhf_wigner_explicit():
    mol = molecule_water_sto3g_angstrom()
    mol.build()

    mf = pyscf.scf.RHF(mol)
    mf.kernel()
    C = utils.fix_mocoeffs_shape(mf.mo_coeff)
    E = utils.fix_moenergies_shape(mf.mo_energy)
    occupations = utils.occupations_from_pyscf_mol(mol, C)
    nocc_alph, nvirt_alph, _, _ = occupations
    nov_alph = nocc_alph * nvirt_alph
    norb = nocc_alph + nvirt_alph

    # calculate linear response vectors for electric dipole operator
    f1 = 0.0
    f2 = 0.0773178
    frequencies = [f1, f2]
    calculator = electric.Polarizability(Program.PySCF,
                                         mol,
                                         C,
                                         E,
                                         occupations,
                                         frequencies=frequencies)
    calculator.form_operators()
    calculator.run()
    calculator.form_results()

    polarizability_1 = calculator.polarizabilities[0]
    polarizability_2 = calculator.polarizabilities[1]
    print("polarizability (static)")
    print(polarizability_1)
    print("polarizability: {} a.u.".format(f2))
    print(polarizability_2)

    # each operator contains multiple sets of response vectors, one
    # set of components for each frequency
    assert isinstance(calculator.driver.solver.operators, list)
    assert len(calculator.driver.solver.operators) == 1
    operator = calculator.driver.solver.operators[0]
    rhsvecs = operator.mo_integrals_ai_supervector_alph
    assert isinstance(operator.rspvecs_alph, list)
    assert len(operator.rspvecs_alph) == 2
    rspvecs_1 = operator.rspvecs_alph[0]
    rspvecs_2 = operator.rspvecs_alph[1]

    ## Form the full [norb, norb] representation of everything.
    # Response vectors: transform X_{ia} and Y_{ia} -> U_{p,q}
    # 0. 'a' is fast index, 'i' slow
    # 1. rspvec == [X Y]
    # 2. U_{p, q} -> zero
    # 3. place X_{ia} into U_{i, a}
    # 4. place Y_{ia} into U_{a, i}

    ncomp = rhsvecs.shape[0]

    rspmats_1 = np.zeros(shape=(ncomp, norb, norb))
    rspmats_2 = np.zeros(shape=(ncomp, norb, norb))
    for i in range(ncomp):
        rspvec_1 = rspvecs_1[i, :, 0]
        rspvec_2 = rspvecs_2[i, :, 0]
        x_1 = rspvec_1[:nov_alph]
        y_1 = rspvec_1[nov_alph:]
        x_2 = rspvec_2[:nov_alph]
        y_2 = rspvec_2[nov_alph:]
        x_full_1 = utils.repack_vector_to_matrix(x_1, (nvirt_alph, nocc_alph))
        y_full_1 = utils.repack_vector_to_matrix(y_1, (nvirt_alph, nocc_alph))
        x_full_2 = utils.repack_vector_to_matrix(x_2, (nvirt_alph, nocc_alph))
        y_full_2 = utils.repack_vector_to_matrix(y_2, (nvirt_alph, nocc_alph))
        rspmats_1[i, :nocc_alph, nocc_alph:] = y_full_1.T
        rspmats_1[i, nocc_alph:, :nocc_alph] = x_full_1
        rspmats_2[i, :nocc_alph, nocc_alph:] = y_full_2.T
        rspmats_2[i, nocc_alph:, :nocc_alph] = x_full_2

    rhsmats = np.zeros(shape=(ncomp, norb, norb))
    for i in range(ncomp):
        rhsvec = rhsvecs[i, :, 0]
        rhsvec_top = rhsvec[:nov_alph]
        rhsvec_bot = rhsvec[nov_alph:]
        rhsvec_top_mat = utils.repack_vector_to_matrix(rhsvec_top,
                                                       (nvirt_alph, nocc_alph))
        rhsvec_bot_mat = utils.repack_vector_to_matrix(rhsvec_bot,
                                                       (nvirt_alph, nocc_alph))
        rhsmats[i, :nocc_alph, nocc_alph:] = rhsvec_top_mat.T
        rhsmats[i, nocc_alph:, :nocc_alph] = rhsvec_bot_mat

    polarizability_full_1 = np.empty_like(polarizability_1)
    polarizability_full_2 = np.empty_like(polarizability_2)
    for a in (0, 1, 2):
        for b in (0, 1, 2):
            polarizability_full_1[a, b] = 2 * np.trace(rhsmats[a, ...].T.dot(
                rspmats_1[b, ...]))
            polarizability_full_2[a, b] = 2 * np.trace(rhsmats[a, ...].T.dot(
                rspmats_2[b, ...]))

    np.testing.assert_almost_equal(polarizability_1, -polarizability_full_1)
    np.testing.assert_almost_equal(polarizability_2, -polarizability_full_2)

    # V_{p,q} <- full MO transformation of right hand side
    integrals_ao = operator.ao_integrals
    integrals_mo = np.empty_like(integrals_ao)
    for i in range(ncomp):
        integrals_mo[i, ...] = (C[0, ...].T).dot(integrals_ao[i,
                                                              ...]).dot(C[0,
                                                                          ...])

    # from pyresponse.ao2mo import AO2MOpyscf
    # ao2mo = AO2MOpyscf(C, pyscfmol=mol)
    # ao2mo.perform_rhf_full()
    # tei_mo = ao2mo.tei_mo[0]

    G_1 = np.empty_like(rspmats_1)
    G_2 = np.empty_like(rspmats_2)
    C = mf.mo_coeff
    # TODO I feel as though if I have all the MO-basis two-electron
    # integrals, I shouldn't need another JK build.
    for i in range(ncomp):
        V = integrals_mo[i, ...]
        Dl_1 = (C[:, :nocc_alph]).dot(rspmats_1[i, :nocc_alph, :]).dot(C.T)
        Dr_1 = (-C).dot(rspmats_1[i, :, :nocc_alph]).dot(C[:, :nocc_alph].T)
        D_1 = Dl_1 + Dr_1
        Dl_2 = (C[:, :nocc_alph]).dot(rspmats_2[i, :nocc_alph, :]).dot(C.T)
        Dr_2 = (-C).dot(rspmats_2[i, :, :nocc_alph]).dot(C[:, :nocc_alph].T)
        D_2 = Dl_2 + Dr_2
        J_1, K_1 = mf.get_jk(mol, D_1, hermi=0)
        J_2, K_2 = mf.get_jk(mol, D_2, hermi=0)
        F_AO_1 = 2 * J_1 - K_1
        F_AO_2 = 2 * J_2 - K_2
        F_MO_1 = (C.T).dot(F_AO_1).dot(C)
        F_MO_2 = (C.T).dot(F_AO_2).dot(C)
        G_1[i, ...] = V + F_MO_1
        G_2[i, ...] = V + F_MO_2

    E_diag = np.diag(E[0, ...])
    epsilon_1 = G_1.copy()
    epsilon_2 = G_2.copy()
    for i in range(ncomp):
        eoU_1 = (E_diag[..., np.newaxis] + f1) * rspmats_1[i, ...]
        Ue_1 = rspmats_1[i, ...] * E_diag[np.newaxis, ...]
        epsilon_1[i, ...] += eoU_1 - Ue_1
        eoU_2 = (E_diag[..., np.newaxis] + f2) * rspmats_2[i, ...]
        Ue_2 = rspmats_2[i, ...] * E_diag[np.newaxis, ...]
        epsilon_2[i, ...] += eoU_2 - Ue_2

    # Assume some symmetry and calculate only part of the tensor.

    hyperpolarizability = np.zeros(shape=(6, 3))
    off1 = [0, 1, 2, 0, 0, 1]
    off2 = [0, 1, 2, 1, 2, 2]
    for r in range(6):
        b = off1[r]
        c = off2[r]
        for a in range(3):
            # _1 -> 0
            # _2 -> +w
            # a is _1, b is _2, c is _2 transposed/negated
            tl1 = np.trace(rspmats_1[a, ...].dot(G_2[b, ...]).dot(
                rspmats_2[c, ...].T)[:nocc_alph, :nocc_alph])
            tl2 = np.trace(rspmats_2[c, ...].T.dot(G_2[b, ...]).dot(
                rspmats_1[a, ...])[:nocc_alph, :nocc_alph])
            tl3 = np.trace(rspmats_1[a, ...].dot(-G_2[c, ...].T).dot(
                rspmats_2[b, ...])[:nocc_alph, :nocc_alph])
            tl4 = np.trace(rspmats_2[b, ...].dot(-G_2[c, ...].T).dot(
                rspmats_1[a, ...])[:nocc_alph, :nocc_alph])
            tl5 = np.trace(rspmats_2[c, ...].T.dot(G_1[a, ...]).dot(
                rspmats_2[b, ...])[:nocc_alph, :nocc_alph])
            tl6 = np.trace(rspmats_2[b, ...].dot(G_1[a, ...]).dot(
                rspmats_2[c, ...].T)[:nocc_alph, :nocc_alph])
            tr1 = np.trace(rspmats_2[c, ...].T.dot(rspmats_2[b, ...]).dot(
                epsilon_1[a, ...])[:nocc_alph, :nocc_alph])
            tr2 = np.trace(rspmats_2[b, ...].dot(rspmats_2[c, ...].T).dot(
                epsilon_1[a, ...])[:nocc_alph, :nocc_alph])
            tr3 = np.trace(rspmats_2[c, ...].T.dot(rspmats_1[a, ...]).dot(
                epsilon_2[b, ...])[:nocc_alph, :nocc_alph])
            tr4 = np.trace(rspmats_1[a, ...].dot(rspmats_2[c, ...].T).dot(
                epsilon_2[b, ...])[:nocc_alph, :nocc_alph])
            tr5 = np.trace(rspmats_2[b, ...].dot(
                rspmats_1[a,
                          ...]).dot(-epsilon_2[c,
                                               ...].T)[:nocc_alph, :nocc_alph])
            tr6 = np.trace(rspmats_1[a, ...].dot(
                rspmats_2[b,
                          ...]).dot(-epsilon_2[c,
                                               ...].T)[:nocc_alph, :nocc_alph])
            tl = tl1 + tl2 + tl3 + tl4 + tl5 + tl6
            tr = tr1 + tr2 + tr3 + tr4 + tr5 + tr6
            hyperpolarizability[r, a] = -2 * (tl - tr)

    # pylint: disable=C0326
    ref = np.array([
        [-9.02854579, 0.92998934, -0.52377445],
        [2.01080066, 5.23470702, -3.01208409],
        [0.66669794, 1.66112712, -0.87205853],
        [0.92021130, 2.01769267, -1.11067223],
        [-0.51824440, -1.11067586, 0.67140102],
        [-1.10887175, -3.00950655, 1.65659586],
    ])
    ref_avgs = np.array([6.34331713, -7.81628395, 4.40251201])
    ref_avg = 10.98699590

    thresh = 4.0e-5
    assert np.all(np.abs(ref - hyperpolarizability) < thresh)

    print("hyperpolarizability: OR, (0; {}, -{}), symmetry-unique components".
          format(f2, f2))
    print(hyperpolarizability)

    return
Exemplo n.º 2
0
def test_first_hyperpolarizability_shg_rhf_wigner_explicit_psi4numpy_pyscf_large():
    mol = molecule_physicists_water_augccpvdz()
    mol.build()

    mf = pyscf.scf.RHF(mol)
    mf.kernel()
    C = utils.fix_mocoeffs_shape(mf.mo_coeff)
    E = utils.fix_moenergies_shape(mf.mo_energy)
    occupations = occupations_from_pyscf_mol(mol, C)
    nocc_alph, nvirt_alph, _, _ = occupations
    nov_alph = nocc_alph * nvirt_alph
    norb = nocc_alph + nvirt_alph

    # calculate linear response vectors for electric dipole operator
    f1 = 0.0773178
    f2 = 2 * f1
    frequencies = [f1, f2]
    calculator = electric.Polarizability(
        Program.PySCF,
        mol,
        cphf.CPHF(solvers.ExactInv(C, E, occupations)),
        C,
        E,
        occupations,
        frequencies=frequencies,
    )
    calculator.form_operators()
    calculator.run(hamiltonian=Hamiltonian.RPA, spin=Spin.singlet)
    calculator.form_results()

    polarizability_1 = calculator.polarizabilities[0]
    polarizability_2 = calculator.polarizabilities[1]
    print("polarizability: {} a.u.".format(f1))
    print(polarizability_1)
    print("polarizability: {} a.u. (frequency doubled)".format(f2))
    print(polarizability_2)

    # each operator contains multiple sets of response vectors, one
    # set of components for each frequency
    assert isinstance(calculator.driver.solver.operators, list)
    assert len(calculator.driver.solver.operators) == 1
    operator = calculator.driver.solver.operators[0]
    rhsvecs = operator.mo_integrals_ai_supervector_alph
    assert isinstance(operator.rspvecs_alph, list)
    assert len(operator.rspvecs_alph) == 2
    rspvecs_1 = operator.rspvecs_alph[0]
    rspvecs_2 = operator.rspvecs_alph[1]

    ## Form the full [norb, norb] representation of everything.
    # Response vectors: transform X_{ia} and Y_{ia} -> U_{p,q}
    # 0. 'a' is fast index, 'i' slow
    # 1. rspvec == [X Y]
    # 2. U_{p, q} -> zero
    # 3. place X_{ia} into U_{i, a}
    # 4. place Y_{ia} into U_{a, i}

    ncomp = rhsvecs.shape[0]

    rspmats_1 = np.zeros(shape=(ncomp, norb, norb))
    rspmats_2 = np.zeros(shape=(ncomp, norb, norb))
    for i in range(ncomp):
        rspvec_1 = rspvecs_1[i, :, 0]
        rspvec_2 = rspvecs_2[i, :, 0]
        x_1 = rspvec_1[:nov_alph]
        y_1 = rspvec_1[nov_alph:]
        x_2 = rspvec_2[:nov_alph]
        y_2 = rspvec_2[nov_alph:]
        x_full_1 = utils.repack_vector_to_matrix(x_1, (nvirt_alph, nocc_alph))
        y_full_1 = utils.repack_vector_to_matrix(y_1, (nvirt_alph, nocc_alph))
        x_full_2 = utils.repack_vector_to_matrix(x_2, (nvirt_alph, nocc_alph))
        y_full_2 = utils.repack_vector_to_matrix(y_2, (nvirt_alph, nocc_alph))
        rspmats_1[i, :nocc_alph, nocc_alph:] = y_full_1.T
        rspmats_1[i, nocc_alph:, :nocc_alph] = x_full_1
        rspmats_2[i, :nocc_alph, nocc_alph:] = y_full_2.T
        rspmats_2[i, nocc_alph:, :nocc_alph] = x_full_2

    rhsmats = np.zeros(shape=(ncomp, norb, norb))
    for i in range(ncomp):
        rhsvec = rhsvecs[i, :, 0]
        rhsvec_top = rhsvec[:nov_alph]
        rhsvec_bot = rhsvec[nov_alph:]
        rhsvec_top_mat = utils.repack_vector_to_matrix(rhsvec_top, (nvirt_alph, nocc_alph))
        rhsvec_bot_mat = utils.repack_vector_to_matrix(rhsvec_bot, (nvirt_alph, nocc_alph))
        rhsmats[i, :nocc_alph, nocc_alph:] = rhsvec_top_mat.T
        rhsmats[i, nocc_alph:, :nocc_alph] = rhsvec_bot_mat

    polarizability_full_1 = np.empty_like(polarizability_1)
    polarizability_full_2 = np.empty_like(polarizability_2)
    for a in (0, 1, 2):
        for b in (0, 1, 2):
            polarizability_full_1[a, b] = 2 * np.trace(np.dot(rhsmats[a].T, rspmats_1[b]))
            polarizability_full_2[a, b] = 2 * np.trace(np.dot(rhsmats[a].T, rspmats_2[b]))

    np.testing.assert_almost_equal(polarizability_1, -polarizability_full_1)
    np.testing.assert_almost_equal(polarizability_2, -polarizability_full_2)

    # V_{p,q} <- full MO transformation of right hand side
    integrals_ao = operator.ao_integrals
    integrals_mo = np.empty_like(integrals_ao)
    for i in range(ncomp):
        integrals_mo[i] = (C[0].T).dot(integrals_ao[i]).dot(C[0])

    G_1 = np.empty_like(rspmats_1)
    G_2 = np.empty_like(rspmats_2)
    C = mf.mo_coeff
    # TODO I feel as though if I have all the MO-basis two-electron
    # integrals, I shouldn't need another JK build.
    for i in range(ncomp):
        V = integrals_mo[i]
        Dl_1 = (C[:, :nocc_alph]).dot(rspmats_1[i, :nocc_alph, :]).dot(C.T)
        Dr_1 = (-C).dot(rspmats_1[i, :, :nocc_alph]).dot(C[:, :nocc_alph].T)
        D_1 = Dl_1 + Dr_1
        Dl_2 = (C[:, :nocc_alph]).dot(rspmats_2[i, :nocc_alph, :]).dot(C.T)
        Dr_2 = (-C).dot(rspmats_2[i, :, :nocc_alph]).dot(C[:, :nocc_alph].T)
        D_2 = Dl_2 + Dr_2
        J_1, K_1 = mf.get_jk(mol, D_1, hermi=0)
        J_2, K_2 = mf.get_jk(mol, D_2, hermi=0)
        F_AO_1 = 2 * J_1 - K_1
        F_AO_2 = 2 * J_2 - K_2
        F_MO_1 = (C.T).dot(F_AO_1).dot(C)
        F_MO_2 = (C.T).dot(F_AO_2).dot(C)
        G_1[i] = V + F_MO_1
        G_2[i] = V + F_MO_2

    E_diag = np.diag(E[0, ...])
    epsilon_1 = G_1.copy()
    epsilon_2 = G_2.copy()
    for i in range(ncomp):
        eoU_1 = (E_diag[..., np.newaxis] + f1) * rspmats_1[i]
        Ue_1 = rspmats_1[i] * E_diag[np.newaxis, ...]
        epsilon_1[i] += eoU_1 - Ue_1
        eoU_2 = (E_diag[..., np.newaxis] + f2) * rspmats_2[i]
        Ue_2 = rspmats_2[i] * E_diag[np.newaxis, ...]
        epsilon_2[i] += eoU_2 - Ue_2

    # Assume some symmetry and calculate only part of the tensor.

    hyperpolarizability = np.zeros(shape=(6, 3))
    off1 = [0, 1, 2, 0, 0, 1]
    off2 = [0, 1, 2, 1, 2, 2]
    for r in range(6):
        b = off1[r]
        c = off2[r]
        for a in range(3):
            tl1 = np.trace(rspmats_2[a].T.dot(G_1[b]).dot(rspmats_1[c])[:nocc_alph, :nocc_alph])
            tl2 = np.trace(rspmats_1[c].dot(G_1[b]).dot(rspmats_2[a].T)[:nocc_alph, :nocc_alph])
            tl3 = np.trace(rspmats_2[a].T.dot(G_1[c]).dot(rspmats_1[b])[:nocc_alph, :nocc_alph])
            tl4 = np.trace(rspmats_1[b].dot(G_1[c]).dot(rspmats_2[a].T)[:nocc_alph, :nocc_alph])
            tl5 = np.trace(rspmats_1[c].dot(-G_2[a].T).dot(rspmats_1[b])[:nocc_alph, :nocc_alph])
            tl6 = np.trace(rspmats_1[b].dot(-G_2[a].T).dot(rspmats_1[c])[:nocc_alph, :nocc_alph])
            tr1 = np.trace(
                rspmats_1[c].dot(rspmats_1[b]).dot(-epsilon_2[a].T)[:nocc_alph, :nocc_alph]
            )
            tr2 = np.trace(
                rspmats_1[b].dot(rspmats_1[c]).dot(-epsilon_2[a].T)[:nocc_alph, :nocc_alph]
            )
            tr3 = np.trace(
                rspmats_1[c].dot(rspmats_2[a].T).dot(epsilon_1[b])[:nocc_alph, :nocc_alph]
            )
            tr4 = np.trace(
                rspmats_2[a].T.dot(rspmats_1[c]).dot(epsilon_1[b])[:nocc_alph, :nocc_alph]
            )
            tr5 = np.trace(
                rspmats_1[b].dot(rspmats_2[a].T).dot(epsilon_1[c])[:nocc_alph, :nocc_alph]
            )
            tr6 = np.trace(
                rspmats_2[a].T.dot(rspmats_1[b]).dot(epsilon_1[c])[:nocc_alph, :nocc_alph]
            )
            tl = tl1 + tl2 + tl3 + tl4 + tl5 + tl6
            tr = tr1 + tr2 + tr3 + tr4 + tr5 + tr6
            hyperpolarizability[r, a] = -2 * (tl - tr)

    # pylint: disable=C0326
    ref = np.array(
        [
            [0.00000000, 0.00000000, 1.92505358],
            [0.00000000, 0.00000000, -31.33652886],
            [0.00000000, 0.00000000, -13.92830863],
            [0.00000000, 0.00000000, 0.00000000],
            [-1.80626084, 0.00000000, 0.00000000],
            [0.00000000, -31.13504192, 0.00000000],
        ]
    )
    ref_avgs = np.array([0.00000000, 0.00000000, 45.69300223])
    ref_avg = 45.69300223
    diff = np.abs(ref - hyperpolarizability)
    print("abs diff")
    print(diff)
    thresh = 2.5e-04
    assert np.all(diff < thresh)

    print("hyperpolarizability: SHG, (-{}; {}, {}), symmetry-unique components".format(f2, f1, f1))
    print(hyperpolarizability)
    print("ref")
    print(ref)

    # Transpose all frequency-doubled quantities (+2w) to get -2w.

    for i in range(ncomp):
        rspmats_2[i] = rspmats_2[i].T
        G_2[i] = -G_2[i].T
        epsilon_2[i] = -epsilon_2[i].T

    # Assume some symmetry and calculate only part of the tensor. This
    # time, work with the in-place manipulated quantities (this tests
    # their correctness).

    mU = (rspmats_2, rspmats_1)
    mG = (G_2, G_1)
    me = (epsilon_2, epsilon_1)

    hyperpolarizability = np.zeros(shape=(6, 3))
    off1 = [0, 1, 2, 0, 0, 1]
    off2 = [0, 1, 2, 1, 2, 2]
    for r in range(6):
        b = off1[r]
        c = off2[r]
        for a in range(3):
            tl1 = np.trace(mU[0][a].dot(mG[1][b]).dot(mU[1][c])[:nocc_alph, :nocc_alph])
            tl2 = np.trace(mU[1][c].dot(mG[1][b]).dot(mU[0][a])[:nocc_alph, :nocc_alph])
            tl3 = np.trace(mU[0][a].dot(mG[1][c]).dot(mU[1][b])[:nocc_alph, :nocc_alph])
            tl4 = np.trace(mU[1][b].dot(mG[1][c]).dot(mU[0][a])[:nocc_alph, :nocc_alph])
            tl5 = np.trace(mU[1][c].dot(mG[0][a]).dot(mU[1][b])[:nocc_alph, :nocc_alph])
            tl6 = np.trace(mU[1][b].dot(mG[0][a]).dot(mU[1][c])[:nocc_alph, :nocc_alph])
            tr1 = np.trace(mU[1][c].dot(mU[1][b]).dot(me[0][a])[:nocc_alph, :nocc_alph])
            tr2 = np.trace(mU[1][b].dot(mU[1][c]).dot(me[0][a])[:nocc_alph, :nocc_alph])
            tr3 = np.trace(mU[1][c].dot(mU[0][a]).dot(me[1][b])[:nocc_alph, :nocc_alph])
            tr4 = np.trace(mU[0][a].dot(mU[1][c]).dot(me[1][b])[:nocc_alph, :nocc_alph])
            tr5 = np.trace(mU[1][b].dot(mU[0][a]).dot(me[1][c])[:nocc_alph, :nocc_alph])
            tr6 = np.trace(mU[0][a].dot(mU[1][b]).dot(me[1][c])[:nocc_alph, :nocc_alph])
            tl = [tl1, tl2, tl3, tl4, tl5, tl6]
            tr = [tr1, tr2, tr3, tr4, tr5, tr6]
            hyperpolarizability[r, a] = -2 * (sum(tl) - sum(tr))

    assert np.all(np.abs(ref - hyperpolarizability) < thresh)

    # Assume no symmetry and calculate the full tensor.

    hyperpolarizability_full = np.zeros(shape=(3, 3, 3))

    # components x, y, z
    for ip, p in enumerate(list(product(range(3), range(3), range(3)))):
        a, b, c = p
        tl, tr = [], []
        # 1st tuple -> index a, b, c (*not* x, y, z!)
        # 2nd tuple -> index frequency (0 -> -2w, 1 -> +w)
        for iq, q in enumerate(list(permutations(zip(p, (0, 1, 1)), 3))):
            d, e, f = q
            tlp = (mU[d[1]][d[0]]).dot(mG[e[1]][e[0]]).dot(mU[f[1]][f[0]])
            tle = np.trace(tlp[:nocc_alph, :nocc_alph])
            tl.append(tle)
            trp = (mU[d[1]][d[0]]).dot(mU[e[1]][e[0]]).dot(me[f[1]][f[0]])
            tre = np.trace(trp[:nocc_alph, :nocc_alph])
            tr.append(tre)
        hyperpolarizability_full[a, b, c] = -2 * (sum(tl) - sum(tr))
    print("hyperpolarizability: SHG, (-{}; {}, {}), full tensor".format(f2, f1, f1))
    print(hyperpolarizability_full)

    # Check that the elements of the reduced and full tensors are
    # equivalent.

    for r in range(6):
        b = off1[r]
        c = off2[r]
        for a in range(3):
            diff = hyperpolarizability[r, a] - hyperpolarizability_full[a, b, c]
            # TODO why not 14?
            assert abs(diff) < 1.0e-13

    # Compute averages and compare to reference.

    avgs, avg = utils.form_first_hyperpolarizability_averages(hyperpolarizability_full)
    assert np.allclose(ref_avgs, avgs, rtol=0, atol=1.0e-3)
    assert np.allclose([ref_avg], [avg], rtol=0, atol=1.0e-3)
    print(avgs)
    print(avg)

    return
Exemplo n.º 3
0
def test_first_hyperpolarizability_static_rhf_wigner_explicit():
    mol = molecule_water_sto3g_angstrom()
    mol.build()

    mf = pyscf.scf.RHF(mol)
    mf.kernel()
    C = utils.fix_mocoeffs_shape(mf.mo_coeff)
    E = utils.fix_moenergies_shape(mf.mo_energy)
    occupations = utils.occupations_from_pyscf_mol(mol, C)
    nocc_alph, nvirt_alph, _, _ = occupations
    nov_alph = nocc_alph * nvirt_alph
    norb = nocc_alph + nvirt_alph

    # calculate linear response vectors for electric dipole operator
    calculator = electric.Polarizability(Program.PySCF,
                                         mol,
                                         C,
                                         E,
                                         occupations,
                                         frequencies=[0.0])
    calculator.form_operators()
    calculator.run()
    calculator.form_results()

    polarizability = calculator.polarizabilities[0]
    print("polarizability (static)")
    print(polarizability)

    operator = calculator.driver.solver.operators[0]
    rhsvecs = operator.mo_integrals_ai_supervector_alph
    rspvecs = operator.rspvecs_alph[0]

    ## Form the full [norb, norb] representation of everything.
    # Response vectors: transform X_{ia} and Y_{ia} -> U_{p,q}
    # 0. 'a' is fast index, 'i' slow
    # 1. rspvec == [X Y]
    # 2. U_{p, q} -> zero
    # 3. place X_{ia} into U_{i, a}
    # 4. place Y_{ia} into U_{a, i}

    ncomp = rhsvecs.shape[0]

    rspmats = np.zeros(shape=(ncomp, norb, norb))
    for i in range(ncomp):
        rspvec = rspvecs[i, :, 0]
        x = rspvec[:nov_alph]
        y = rspvec[nov_alph:]
        x_full = utils.repack_vector_to_matrix(x, (nvirt_alph, nocc_alph))
        y_full = utils.repack_vector_to_matrix(y, (nvirt_alph, nocc_alph))
        rspmats[i, :nocc_alph, nocc_alph:] = x_full.T
        rspmats[i, nocc_alph:, :nocc_alph] = y_full

    rhsmats = np.zeros(shape=(ncomp, norb, norb))
    for i in range(ncomp):
        rhsvec = rhsvecs[i, :, 0]
        rhsvec_top = rhsvec[:nov_alph]
        rhsvec_bot = rhsvec[nov_alph:]
        rhsvec_top_mat = utils.repack_vector_to_matrix(rhsvec_top,
                                                       (nvirt_alph, nocc_alph))
        rhsvec_bot_mat = utils.repack_vector_to_matrix(rhsvec_bot,
                                                       (nvirt_alph, nocc_alph))
        rhsmats[i, :nocc_alph, nocc_alph:] = rhsvec_top_mat.T
        rhsmats[i, nocc_alph:, :nocc_alph] = rhsvec_bot_mat

    polarizability_full = np.empty_like(polarizability)
    for a in (0, 1, 2):
        for b in (0, 1, 2):
            polarizability_full[a, b] = 2 * np.trace(rhsmats[a, ...].T.dot(
                rspmats[b, ...]))

    np.testing.assert_almost_equal(polarizability, polarizability_full)

    # V_{p,q} <- full MO transformation of right hand side
    integrals_ao = operator.ao_integrals
    integrals_mo = np.empty_like(integrals_ao)
    for i in range(ncomp):
        integrals_mo[i, ...] = (C[0, ...].T).dot(integrals_ao[i,
                                                              ...]).dot(C[0,
                                                                          ...])

    G = np.empty_like(rspmats)
    C = mf.mo_coeff
    # TODO I feel as though if I have all the MO-basis two-electron
    # integrals, I shouldn't need another JK build.
    for i in range(ncomp):
        V = integrals_mo[i, ...]
        Dl = (C[:, nocc_alph:].dot(
            utils.repack_vector_to_matrix(rspvecs[i, :nov_alph, 0],
                                          (nvirt_alph, nocc_alph))).dot(
                                              C[:, :nocc_alph].T))
        J, K = mf.get_jk(mol, Dl, hermi=0)
        F_AO = -(4 * J - K - K.T)
        F_MO = (C.T).dot(F_AO).dot(C)
        G[i, ...] = V + F_MO

    E_diag = np.diag(E[0, ...])
    epsilon = G.copy()
    omega = 0
    for i in range(ncomp):
        eoU = (E_diag[..., np.newaxis] + omega) * rspmats[i, ...]
        Ue = rspmats[i, ...] * E_diag[np.newaxis, ...]
        epsilon[i, ...] += eoU - Ue

    # Assume some symmetry and calculate only part of the tensor.

    hyperpolarizability = np.zeros(shape=(6, 3))
    off1 = [0, 1, 2, 0, 0, 1]
    off2 = [0, 1, 2, 1, 2, 2]
    for r in range(6):
        b = off1[r]
        c = off2[r]
        for a in range(3):
            tl1 = 2 * np.trace(rspmats[a, ...].dot(G[b, ...]).dot(
                rspmats[c, ...])[:nocc_alph, :nocc_alph])
            tl2 = 2 * np.trace(rspmats[a, ...].dot(G[c, ...]).dot(
                rspmats[b, ...])[:nocc_alph, :nocc_alph])
            tl3 = 2 * np.trace(rspmats[c, ...].dot(G[a, ...]).dot(
                rspmats[b, ...])[:nocc_alph, :nocc_alph])
            tr1 = np.trace(rspmats[c, ...].dot(rspmats[b, ...]).dot(
                epsilon[a, ...])[:nocc_alph, :nocc_alph])
            tr2 = np.trace(rspmats[b, ...].dot(rspmats[c, ...]).dot(
                epsilon[a, ...])[:nocc_alph, :nocc_alph])
            tr3 = np.trace(rspmats[c, ...].dot(rspmats[a, ...]).dot(
                epsilon[b, ...])[:nocc_alph, :nocc_alph])
            tr4 = np.trace(rspmats[a, ...].dot(rspmats[c, ...]).dot(
                epsilon[b, ...])[:nocc_alph, :nocc_alph])
            tr5 = np.trace(rspmats[b, ...].dot(rspmats[a, ...]).dot(
                epsilon[c, ...])[:nocc_alph, :nocc_alph])
            tr6 = np.trace(rspmats[a, ...].dot(rspmats[b, ...]).dot(
                epsilon[c, ...])[:nocc_alph, :nocc_alph])
            tl = tl1 + tl2 + tl3
            tr = tr1 + tr2 + tr3 + tr4 + tr5 + tr6
            hyperpolarizability[r, a] = 2 * (tl - tr)

    # pylint: disable=C0326
    ref = np.array([
        [-8.86822254, 0.90192130, -0.50796586],
        [1.98744058, 5.13635628, -2.95319400],
        [0.66008119, 1.62699646, -0.85632412],
        [0.90192130, 1.98744058, -1.09505123],
        [-0.50796586, -1.09505123, 0.66008119],
        [-1.09505123, -2.95319400, 1.62699646],
    ])
    ref_avgs = np.array([6.22070078, -7.66527404, 4.31748398])
    ref_avg = 10.77470242

    thresh = 1.5e-4
    assert np.all(np.abs(ref - hyperpolarizability) < thresh)

    print("hyperpolarizability (static), symmetry-unique components")
    print(hyperpolarizability)

    # Assume no symmetry and calculate the full tensor.

    hyperpolarizability_full = np.zeros(shape=(3, 3, 3))
    for p in product(range(3), range(3), range(3)):
        a, b, c = p
        tl, tr = 0, 0
        for q in permutations(p, 3):
            d, e, f = q
            tl += np.trace(rspmats[d, ...].dot(G[e, ...]).dot(
                rspmats[f, ...])[:nocc_alph, :nocc_alph])
            tr += np.trace(rspmats[d, ...].dot(rspmats[e, ...]).dot(
                epsilon[f, ...])[:nocc_alph, :nocc_alph])
        hyperpolarizability_full[a, b, c] = 2 * (tl - tr)
    print("hyperpolarizability (static), full tensor")
    print(hyperpolarizability_full)

    # Check that the elements of the reduced and full tensors are
    # equivalent.

    thresh = 1.0e-14
    for r in range(6):
        b = off1[r]
        c = off2[r]
        for a in range(3):
            diff = hyperpolarizability[r, a] - hyperpolarizability_full[a, b,
                                                                        c]
            assert abs(diff) < thresh

    # Compute averages and compare to reference.
    # This is the slow way.
    # avgs = []
    # for i in range(3):
    #     avg_c = 0
    #     for j in range(3):
    #         avg_c += hyperpolarizability_full[i, j, j] + hyperpolarizability_full[j, i, j] + hyperpolarizability_full[j, j, i]
    #     avgs.append((-1/3) * avg_c)
    # print(np.asarray(avgs))
    x = hyperpolarizability_full
    # This is the simplest non-einsum way.
    # avgs = (-1 / 3) * np.asarray([np.trace(x[i, :, :] + x[:, i, :] + x[:, :, i]) for i in range(3)])
    # This is the best way.
    avgs = (-1 / 3) * (np.einsum("ijj->i", x) + np.einsum("jij->i", x) +
                       np.einsum("jji->i", x))
    # print(list(set([''.join(p) for p in list(permutations('ijj', 3))])))
    assert np.allclose(ref_avgs, avgs, rtol=0, atol=1.0e-3)
    avg = np.sum(avgs**2)**(1 / 2)
    assert np.allclose([ref_avg], [avg], rtol=0, atol=1.0e-3)
    print(avgs)
    print(avg)

    utils_avgs, utils_avg = utils.form_first_hyperpolarizability_averages(x)
    assert np.allclose(avgs, utils_avgs, rtol=0, atol=1.0e-13)
    assert np.allclose([avg], [utils_avg], rtol=0, atol=1.0e-13)

    return