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[Ready for review] Complete implementation of pbc/tdscf (pyscf#1793)
* Bug fix for RSDF due to Mole basis sorting * Bug fix for pbc df Jbuild for hermi == 0 * improve TDSCF init guess degeneracy handle * complete pbc tdscf * b3lyp -> b3lyp5 * adjust values due to v2.3 * add examples; add finalize * remove non-gamma point exception * fix flake8 error * remove numer instable tests (higher roots) * update tests * fix wrong num of states * bug fix in response * keep minimal changes for pbc _response * better handle of exxdiv, including vcut * add NotImplementedError for rsjk + non-zero kshift * fix shifted kpt for TDRKS/UKS * fix flake8 error * revert CasidaTDDFT * fix flake error --------- Co-authored-by: hongzhouye <>
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,65 +1,91 @@ | ||
| #!/usr/bin/env python | ||
| # | ||
| # Author: Hong-Zhou Ye <[email protected]> | ||
| # | ||
|
|
||
| ''' | ||
| TDDFT with k-point sampling or at an individual k-point | ||
| import numpy as np | ||
| from pyscf.pbc import gto, scf, tdscf | ||
| from pyscf import scf as molscf | ||
| from pyscf import lib | ||
|
|
||
| (This feature is in testing. We observe numerical stability problem in TDDFT | ||
| diagonalization.) | ||
|
|
||
| ''' | ||
| TDSCF with k-point sampling | ||
| ''' | ||
| atom = 'C 0 0 0; C 0.8925000000 0.8925000000 0.8925000000' | ||
| a = ''' | ||
| 1.7850000000 1.7850000000 0.0000000000 | ||
| 0.0000000000 1.7850000000 1.7850000000 | ||
| 1.7850000000 0.0000000000 1.7850000000 | ||
| ''' | ||
| basis = ''' | ||
| C S | ||
| 9.031436 -1.960629e-02 | ||
| 3.821255 -1.291762e-01 | ||
| 0.473725 5.822572e-01 | ||
| C P | ||
| 4.353457 8.730943e-02 | ||
| 1.266307 2.797034e-01 | ||
| 0.398715 5.024424e-01 | ||
| ''' # a trimmed DZ basis for fast test | ||
| pseudo = 'gth-hf-rev' | ||
| cell = gto.M(atom=atom, basis=basis, a=a, pseudo=pseudo).set(verbose=3) | ||
| kmesh = [2,1,1] | ||
| kpts = cell.make_kpts(kmesh) | ||
| nkpts = len(kpts) | ||
| mf = scf.KRHF(cell, kpts).rs_density_fit().run() | ||
|
|
||
| from pyscf.pbc import gto | ||
| from pyscf.pbc import scf | ||
| from pyscf.pbc import df | ||
| from pyscf.pbc import tdscf | ||
| log = lib.logger.new_logger(mf) | ||
|
|
||
| cell = gto.Cell() | ||
| cell.unit = 'B' | ||
| cell.atom = ''' | ||
| C 0. 0. 0. | ||
| C 1.68506879 1.68506879 1.68506879 | ||
| ''' | ||
| cell.a = ''' | ||
| 0. 3.37013758 3.37013758 | ||
| 3.37013758 0. 3.37013758 | ||
| 3.37013758 3.37013758 0. | ||
| ''' k-point TDSCF solutions can have non-zero momentum transfer between particle and hole. | ||
| This can be controlled by `td.kshift_lst`. By default, kshift_lst = [0] and only the | ||
| zero-momentum transfer solution (i.e., 'vertical' in k-space) will be solved, as | ||
| demonstrated in the example below. | ||
| ''' | ||
| cell.basis = 'gth-szv' | ||
| cell.pseudo = 'gth-pade' | ||
| cell.build() | ||
| mf = scf.KRHF(cell, cell.make_kpts([2,2,2])) | ||
| mf.run() | ||
| td = mf.TDA().set(nstates=5).run() | ||
| log.note('RHF-TDA:') | ||
| for kshift,es in zip(td.kshift_lst,td.e): | ||
| log.note('kshift = %d Eex = %s', kshift, ' '.join([f'{e:.3f}' for e in es*27.2114])) | ||
|
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||
| td = tdscf.KTDA(mf) | ||
| td.nstates = 5 | ||
| td.verbose = 5 | ||
| print(td.kernel()[0] * 27.2114) | ||
| ''' If GDF/RSDF is used as the density fitting method (as in this example), solutions | ||
| with non-zero particle-hole momentum-transfer solution is also possible. The example | ||
| below demonstrates how to calculate solutions with all possible kshift. | ||
| td = tdscf.KTDDFT(mf) | ||
| td.nstates = 5 | ||
| td.verbose = 5 | ||
| print(td.kernel()[0] * 27.2114) | ||
| NOTE: if FFTDF is used, pyscf will set `kshift_lst` to [0]. | ||
| ''' | ||
| td = mf.TDHF().set(nstates=5, kshift_lst=list(range(nkpts))).run() | ||
| log.note('RHF-TDHF:') | ||
| for kshift,es in zip(td.kshift_lst,td.e): | ||
| log.note('kshift = %d Eex = %s', kshift, ' '.join([f'{e:.3f}' for e in es*27.2114])) | ||
|
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||
| mf = scf.RHF(cell) | ||
| mf.kernel() | ||
| td = tdscf.TDA(mf) | ||
| td.kernel() | ||
|
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||
| # | ||
| # Gamma-point RKS | ||
| # | ||
| ks = scf.RKS(cell) | ||
| ks.run() | ||
| ''' TDHF at a single k-point compared to molecular TDSCF | ||
| ''' | ||
| atom = ''' | ||
| O 0.00000 0.00000 0.11779 | ||
| H 0.00000 0.75545 -0.47116 | ||
| H 0.00000 -0.75545 -0.47116 | ||
| ''' | ||
| a = np.eye(3) * 20 # big box to match isolated molecule | ||
| basis = 'sto-3g' | ||
| auxbasis = 'weigend' | ||
| cell = gto.M(atom=atom, basis=basis, a=a).set(verbose=3) | ||
| mol = cell.to_mol() | ||
|
|
||
| td = tdscf.KTDDFT(ks) | ||
| td.nstates = 5 | ||
| td.verbose = 5 | ||
| print(td.kernel()[0] * 27.2114) | ||
| log = lib.logger.new_logger(cell) | ||
|
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||
| xc = 'b3lyp' | ||
| # pbc | ||
| mf = scf.RKS(cell).set(xc=xc).rs_density_fit(auxbasis=auxbasis).run() | ||
| pbctda = mf.TDA().run() | ||
| pbctd = mf.TDDFT().run() | ||
| # mol | ||
| molmf = molscf.RKS(cell).set(xc=xc).density_fit(auxbasis=auxbasis).run() | ||
| moltda = molmf.TDA().run() | ||
| moltd = molmf.TDDFT().run() | ||
|
|
||
| # TODO: | ||
| #kpt = cell.get_abs_kpts([0.25, 0.25, 0.25]) | ||
| #mf = scf.RHF(cell, kpt=kpt) | ||
| #mf.kernel() | ||
| #td = tdscf.TDA(mf) | ||
| #td.kernel() | ||
| _format = lambda e: ' '.join([f'{x*27.2114:.3f}' for x in e]) | ||
| log.note('PBC TDA : %s', _format(pbctda.e)) | ||
| log.note('Mol TDA : %s', _format(moltda.e)) | ||
| log.note('PBC TDDFT: %s', _format(pbctd.e)) | ||
| log.note('Mol TDDFT: %s', _format(moltd.e)) |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,46 @@ | ||
| #!/usr/bin/env python | ||
| # | ||
| # Author: Hong-Zhou Ye <[email protected]> | ||
| # | ||
|
|
||
|
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||
| from pyscf import gto, scf, tdscf | ||
|
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||
|
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| ''' TDSCF selected particle-hole pairs that have low energy difference (e.g., HOMO -> LUMO, | ||
| HOMO -> LUMO+1 etc.) as init guess for the iterative solution of the TDSCF equation. | ||
| In cases where there are many near degenerate p-h pairs, their contributions to the | ||
| final TDSCF solutions can all be significnat and all such pairs should be included. | ||
| The determination of such near degeneracies in p-h pairs is controlled by the | ||
| `deg_eia_thresh` variable: if the excitation energy of two p-h pairs differs less | ||
| than `deg_eia_thresh`, they will be considered degenerate and selected simultaneously | ||
| as init guess. | ||
| This example demonstrates the use of this variable to reduce the chance of missing | ||
| roots in TDSCF calculations. A molecule is used here for demonstration but the same | ||
| applies to periodic TDSCF calculations. | ||
| ''' | ||
|
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||
| atom = ''' | ||
| O 0.00000 0.00000 0.11779 | ||
| H 0.00000 0.75545 -0.47116 | ||
| H 0.00000 -0.75545 -0.47116 | ||
| O 4.00000 0.00000 0.11779 | ||
| H 4.00000 0.75545 -0.47116 | ||
| H 4.00000 -0.75545 -0.47116 | ||
| ''' | ||
| basis = 'cc-pvdz' | ||
|
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| mol = gto.M(atom=atom, basis=basis) | ||
| mf = scf.RHF(mol).density_fit().run() | ||
|
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| ''' By default, `deg_eia_thresh` = 1e-3 (Ha) as can be seen in the output if verbose >= 4. | ||
| ''' | ||
| mf.TDA().set(nroots=6).run() | ||
|
|
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| ''' One can check if there are missing roots by using a larger value for `deg_eia_thresh`. | ||
| Note that this will increase the number of init guess vectors and increase the cost of | ||
| solving the TDSCF equation. | ||
| ''' | ||
| mf.TDA().set(nroots=6, deg_eia_thresh=0.1).run() |
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