pyscf.adc package#

Submodules#

pyscf.adc.dfadc module#

pyscf.adc.dfadc.get_ovvv_df(myadc, Lov, Lvv, p, chnk_size)[source]#: Returns approximate ovvv integrals used in restricted implementation

pyscf.adc.dfadc.get_ovvv_spin_df(myadc, Lov, Lvv, p, chnk_size)[source]#: Returns approximate ovvv integrals (different spin cases) used in unrestricted implementation

pyscf.adc.dfadc.get_vVvV_df(myadc, Lvv, LVV, p, chnk_size)[source]#: Returns approximate vvvv integrals (mixed spin) used in unrestricted implementation

pyscf.adc.dfadc.get_vvvv_antisym_df(myadc, Lvv, p, chnk_size, pack=True)[source]#: Returns approximate antisymmetrized vvvv integrals (alpha/beta spin) used in unrestricted implementation

pyscf.adc.dfadc.get_vvvv_df(myadc, Lvv, p, chnk_size)[source]#: Returns approximate vvvv integrals used in restricted implementation

pyscf.adc.radc module#

Restricted algebraic diagrammatic construction

class pyscf.adc.radc.RADC(mf, frozen=0, mo_coeff=None, mo_occ=None)[source]#

Bases: StreamObject

Ground state calculations

Attributes:

verboseint

Print level. Default value equals to Mole.verbose

max_memoryfloat or int

Allowed memory in MB. Default value equals to Mole.max_memory

incore_completebool

Avoid all I/O. Default is False.

methodstring

nth-order ADC method. Options are : ADC(2), ADC(2)-X, ADC(3). Default is ADC(2).

>>> mol = gto.M(atom = 'H 0 0 0; F 0 0 1.1', basis = 'ccpvdz')
>>> mf = scf.RHF(mol).run()
>>> myadc = adc.RADC(mf).run()

Saved results

e_corrfloat
MPn correlation correction

e_totfloat
Total energy (HF + correlation)

t1, t2 :
T amplitudes t1[i,a], t2[i,j,a,b] (i,j in occ, a,b in virt)

analyze()[source]#

async_io = True#

blkmin = 4#

compute_amplitudes(eris)#

compute_dyson_mo()[source]#

compute_energy(t2, eris)#

density_fit(auxbasis=None, with_df=None)[source]#

dump_flags(verbose=None)[source]#

dump_flags_gs(verbose=None)[source]#

ea_adc(nroots=1, guess=None, eris=None)[source]#

incore_complete = False#

ip_adc(nroots=1, guess=None, eris=None)[source]#

ip_cvs_adc(nroots=1, guess=None, eris=None)[source]#

kernel(nroots=1, guess=None, eris=None)[source]#: Kernel function is the main driver of a method. Every method should define the kernel function as the entry of the calculation. Note the return value of kernel function is not strictly defined. It can be anything related to the method (such as the energy, the wave-function, the DFT mesh grids etc.).

kernel_gs()[source]#

make_rdm1()[source]#

make_ref_rdm1()#

memorymin = 2000#

transform_integrals()#

pyscf.adc.radc.kernel(adc, nroots=1, guess=None, eris=None, verbose=None)[source]#

pyscf.adc.radc.make_ref_rdm1(adc)[source]#

pyscf.adc.radc_amplitudes module#

Restricted algebraic diagrammatic construction

pyscf.adc.radc_amplitudes.compute_amplitudes(myadc, eris)[source]#

pyscf.adc.radc_amplitudes.compute_amplitudes_energy(myadc, eris, verbose=None)[source]#

pyscf.adc.radc_amplitudes.compute_energy(myadc, t2, eris)[source]#

pyscf.adc.radc_amplitudes.contract_ladder(myadc, t_amp, vvvv)[source]#

pyscf.adc.radc_ao2mo module#

pyscf.adc.radc_ao2mo.calculate_chunk_size(myadc)[source]#

pyscf.adc.radc_ao2mo.transform_integrals_df(myadc)[source]#

pyscf.adc.radc_ao2mo.transform_integrals_incore(myadc)[source]#

pyscf.adc.radc_ao2mo.transform_integrals_outcore(myadc)[source]#

pyscf.adc.radc_ao2mo.unpack_eri_1(eri, norb)[source]#

pyscf.adc.radc_ao2mo.unpack_eri_2(eri, norb)[source]#

pyscf.adc.radc_ea module#

Restricted algebraic diagrammatic construction

class pyscf.adc.radc_ea.RADCEA(adc)[source]#

Bases: RADC

restricted ADC for EA energies and spectroscopic amplitudes

Attributes:

verboseint: Print level. Default value equals to Mole.verbose
max_memoryfloat or int: Allowed memory in MB. Default value equals to Mole.max_memory
incore_completebool: Avoid all I/O. Default is False.
methodstring: nth-order ADC method. Options are : ADC(2), ADC(2)-X, ADC(3). Default is ADC(2).
conv_tolfloat: Convergence threshold for Davidson iterations. Default is 1e-12.
max_cycleint: Number of Davidson iterations. Default is 50.
max_spaceint: Space size to hold trial vectors for Davidson iterative diagonalization. Default is 12.

Kwargs:

nrootsint

Number of roots (eigenvalues) requested. Default value is 1.

>>> myadc = adc.RADC(mf).run()
>>> myadcea = adc.RADC(myadc).run()

Saved results

e_eafloat or list of floats
EA energy (eigenvalue). For nroots = 1, it is a single float number. If nroots > 1, it is a list of floats for the lowest nroots eigenvalues.

v_iparray
Eigenvectors for each EA transition.

p_eafloat
Spectroscopic amplitudes for each EA transition.

analyze()#

analyze_eigenvector()#

analyze_spec_factor()#

compute_dyson_mo()#

gen_matvec(imds=None, eris=None)[source]#

get_diag(M_ab=None, eris=None)#

get_imds(eris=None)#

get_init_guess(nroots=1, diag=None, ascending=True)[source]#

get_properties(nroots=1)#

get_trans_moments()#

kernel(nroots=1, guess=None, eris=None, verbose=None)#: Kernel function is the main driver of a method. Every method should define the kernel function as the entry of the calculation. Note the return value of kernel function is not strictly defined. It can be anything related to the method (such as the energy, the wave-function, the DFT mesh grids etc.).

make_rdm1()#

matvec(M_ab=None, eris=None)#

renormalize_eigenvectors(nroots=1)#

pyscf.adc.radc_ea.analyze(myadc)[source]#

pyscf.adc.radc_ea.analyze_eigenvector(adc)[source]#

pyscf.adc.radc_ea.analyze_spec_factor(adc)[source]#

pyscf.adc.radc_ea.compute_dyson_mo(myadc)[source]#

pyscf.adc.radc_ea.contract_r_vvvv(myadc, r2, vvvv)[source]#

pyscf.adc.radc_ea.get_diag(adc, M_ab=None, eris=None)[source]#

pyscf.adc.radc_ea.get_imds(adc, eris=None)[source]#

pyscf.adc.radc_ea.get_properties(adc, nroots=1)[source]#

pyscf.adc.radc_ea.get_trans_moments(adc)[source]#

pyscf.adc.radc_ea.get_trans_moments_orbital(adc, orb)[source]#

pyscf.adc.radc_ea.make_rdm1(adc)[source]#

pyscf.adc.radc_ea.make_rdm1_eigenvectors(adc, L, R)[source]#

pyscf.adc.radc_ea.matvec(adc, M_ab=None, eris=None)[source]#

pyscf.adc.radc_ea.renormalize_eigenvectors(adc, nroots=1)[source]#

pyscf.adc.radc_ip module#

Restricted algebraic diagrammatic construction

class pyscf.adc.radc_ip.RADCIP(adc)[source]#

Bases: RADC

restricted ADC for IP energies and spectroscopic amplitudes

Attributes:

verboseint: Print level. Default value equals to Mole.verbose
max_memoryfloat or int: Allowed memory in MB. Default value equals to Mole.max_memory
incore_completebool: Avoid all I/O. Default is False.
methodstring: nth-order ADC method. Options are : ADC(2), ADC(2)-X, ADC(3). Default is ADC(2).
conv_tolfloat: Convergence threshold for Davidson iterations. Default is 1e-12.
max_cycleint: Number of Davidson iterations. Default is 50.
max_spaceint: Space size to hold trial vectors for Davidson iterative diagonalization. Default is 12.

Kwargs:

nrootsint

Number of roots (eigenvalues) requested. Default value is 1.

>>> myadc = adc.RADC(mf).run()
>>> myadcip = adc.RADC(myadc).run()

Saved results

e_ipfloat or list of floats
IP energy (eigenvalue). For nroots = 1, it is a single float number. If nroots > 1, it is a list of floats for the lowest nroots eigenvalues.

v_iparray
Eigenvectors for each IP transition.

p_ipfloat
Spectroscopic amplitudes for each IP transition.

analyze()#

analyze_eigenvector()#

analyze_spec_factor()#

compute_dyson_mo()#

gen_matvec(imds=None, eris=None)[source]#

get_diag(M_ij=None, eris=None)#

get_imds(eris=None)#

get_init_guess(nroots=1, diag=None, ascending=True)[source]#

get_properties(nroots=1)#

get_trans_moments()#

kernel(nroots=1, guess=None, eris=None, verbose=None)#: Kernel function is the main driver of a method. Every method should define the kernel function as the entry of the calculation. Note the return value of kernel function is not strictly defined. It can be anything related to the method (such as the energy, the wave-function, the DFT mesh grids etc.).

make_rdm1()#

matvec(M_ij=None, eris=None)#

renormalize_eigenvectors(nroots=1)#

pyscf.adc.radc_ip.analyze(myadc)[source]#

pyscf.adc.radc_ip.analyze_eigenvector(adc)[source]#

pyscf.adc.radc_ip.analyze_spec_factor(adc)[source]#

pyscf.adc.radc_ip.compute_dyson_mo(myadc)[source]#

pyscf.adc.radc_ip.get_diag(adc, M_ij=None, eris=None)[source]#

pyscf.adc.radc_ip.get_imds(adc, eris=None)[source]#

pyscf.adc.radc_ip.get_properties(adc, nroots=1)[source]#

pyscf.adc.radc_ip.get_trans_moments(adc)[source]#

pyscf.adc.radc_ip.get_trans_moments_orbital(adc, orb)[source]#

pyscf.adc.radc_ip.make_rdm1(adc)[source]#

pyscf.adc.radc_ip.make_rdm1_eigenvectors(adc, L, R)[source]#

pyscf.adc.radc_ip.matvec(adc, M_ij=None, eris=None)[source]#

pyscf.adc.radc_ip.renormalize_eigenvectors(adc, nroots=1)[source]#

pyscf.adc.radc_ip_cvs module#

Restricted algebraic diagrammatic construction

class pyscf.adc.radc_ip_cvs.RADCIPCVS(adc)[source]#

Bases: RADC

restricted ADC for IP-CVS energies and spectroscopic amplitudes

Attributes:

verboseint: Print level. Default value equals to Mole.verbose
max_memoryfloat or int: Allowed memory in MB. Default value equals to Mole.max_memory
incore_completebool: Avoid all I/O. Default is False.
methodstring: nth-order ADC method. Options are : ADC(2), ADC(2)-X, ADC(3). Default is ADC(2).
conv_tolfloat: Convergence threshold for Davidson iterations. Default is 1e-12.
max_cycleint: Number of Davidson iterations. Default is 50.
max_spaceint: Space size to hold trial vectors for Davidson iterative diagonalization. Default is 12.

Kwargs:

nrootsint

Number of roots (eigenvalues) requested. Default value is 1.

>>> myadc = adc.RADC(mf).run()
>>> myadcip = adc.RADC(myadc).run()

Saved results

e_ipfloat or list of floats
IP energy (eigenvalue). For nroots = 1, it is a single float number. If nroots > 1, it is a list of floats for the lowest nroots eigenvalues.

v_iparray
Eigenvectors for each IP transition.

p_ipfloat
Spectroscopic amplitudes for each IP transition.

analyze()#

analyze_spec_factor()#

compute_dyson_mo()#

gen_matvec(imds=None, eris=None)[source]#

get_diag(M_ij=None, eris=None)#

get_imds(eris=None)#

get_init_guess(nroots=1, diag=None, ascending=True)[source]#

get_properties(nroots=1)#

get_trans_moments()#

kernel(nroots=1, guess=None, eris=None, verbose=None)#: Kernel function is the main driver of a method. Every method should define the kernel function as the entry of the calculation. Note the return value of kernel function is not strictly defined. It can be anything related to the method (such as the energy, the wave-function, the DFT mesh grids etc.).

matvec(M_ij=None, eris=None)#

renormalize_eigenvectors(nroots=1)#

pyscf.adc.radc_ip_cvs.analyze(myadc)[source]#

pyscf.adc.radc_ip_cvs.analyze_spec_factor(adc)[source]#

pyscf.adc.radc_ip_cvs.compute_dyson_mo(myadc)[source]#

pyscf.adc.radc_ip_cvs.get_diag(adc, M_ij=None, eris=None)[source]#

pyscf.adc.radc_ip_cvs.get_imds(adc, eris=None)[source]#

pyscf.adc.radc_ip_cvs.get_properties(adc, nroots=1)[source]#

pyscf.adc.radc_ip_cvs.get_trans_moments(adc)[source]#

pyscf.adc.radc_ip_cvs.get_trans_moments_orbital(adc, orb)[source]#

pyscf.adc.radc_ip_cvs.matvec(adc, M_ij=None, eris=None)[source]#

pyscf.adc.radc_ip_cvs.renormalize_eigenvectors(adc, nroots=1)[source]#

pyscf.adc.uadc module#

Unrestricted algebraic diagrammatic construction

class pyscf.adc.uadc.UADC(mf, frozen=None, mo_coeff=None, mo_occ=None)[source]#

Bases: StreamObject

Ground state calculations

Attributes:

verboseint

Print level. Default value equals to Mole.verbose

max_memoryfloat or int

Allowed memory in MB. Default value equals to Mole.max_memory

incore_completebool

Avoid all I/O. Default is False.

methodstring

nth-order ADC method. Options are : ADC(2), ADC(2)-X, ADC(3). Default is ADC(2).

>>> mol = gto.M(atom = 'H 0 0 0; F 0 0 1.1', basis = 'ccpvdz')
>>> mf = scf.RHF(mol).run()
>>> myadc = adc.UADC(mf).run()

Saved results

e_corrfloat
MPn correlation correction

e_totfloat
Total energy (HF + correlation)

t1, t2 :
T amplitudes t1[i,a], t2[i,j,a,b] (i,j in occ, a,b in virt)

analyze()[source]#

compute_amplitudes(eris)#

compute_dyson_mo()[source]#

compute_energy(t1, t2, eris)#

density_fit(auxbasis=None, with_df=None)[source]#

dump_flags(verbose=None)[source]#

dump_flags_gs(verbose=None)[source]#

ea_adc(nroots=1, guess=None, eris=None)[source]#

incore_complete = False#

ip_adc(nroots=1, guess=None, eris=None)[source]#

ip_cvs_adc(nroots=1, guess=None, eris=None)[source]#

kernel(nroots=1, guess=None, eris=None)[source]#: Kernel function is the main driver of a method. Every method should define the kernel function as the entry of the calculation. Note the return value of kernel function is not strictly defined. It can be anything related to the method (such as the energy, the wave-function, the DFT mesh grids etc.).

kernel_gs()[source]#

make_rdm1()[source]#

semi_canonicalize_orbitals(f, nocc, C)[source]#

transform_integrals()#

pyscf.adc.uadc.kernel(adc, nroots=1, guess=None, eris=None, verbose=None)[source]#

pyscf.adc.uadc_amplitudes module#

Unrestricted algebraic diagrammatic construction

pyscf.adc.uadc_amplitudes.compute_amplitudes(myadc, eris)[source]#

pyscf.adc.uadc_amplitudes.compute_amplitudes_energy(myadc, eris, verbose=None)[source]#

pyscf.adc.uadc_amplitudes.compute_energy(myadc, t1, t2, eris)[source]#

pyscf.adc.uadc_amplitudes.contract_ladder(myadc, t_amp, vvvv_p, prefactor=1.0, pack=False)[source]#

pyscf.adc.uadc_amplitudes.contract_ladder_antisym(myadc, t_amp, vvvv_d, pack=True)[source]#

pyscf.adc.uadc_ao2mo module#

pyscf.adc.uadc_ao2mo.calculate_chunk_size(myadc)[source]#

pyscf.adc.uadc_ao2mo.transform_integrals_df(myadc)[source]#

pyscf.adc.uadc_ao2mo.transform_integrals_incore(myadc)[source]#

pyscf.adc.uadc_ao2mo.transform_integrals_outcore(myadc)[source]#

pyscf.adc.uadc_ao2mo.unpack_eri_1(eri, norb)[source]#

pyscf.adc.uadc_ea module#

Unrestricted algebraic diagrammatic construction

class pyscf.adc.uadc_ea.UADCEA(adc)[source]#

Bases: UADC

unrestricted ADC for EA energies and spectroscopic amplitudes

Attributes:

verboseint: Print level. Default value equals to Mole.verbose
max_memoryfloat or int: Allowed memory in MB. Default value equals to Mole.max_memory
incore_completebool: Avoid all I/O. Default is False.
methodstring: nth-order ADC method. Options are : ADC(2), ADC(2)-X, ADC(3). Default is ADC(2).
conv_tolfloat: Convergence threshold for Davidson iterations. Default is 1e-12.
max_cycleint: Number of Davidson iterations. Default is 50.
max_spaceint: Space size to hold trial vectors for Davidson iterative diagonalization. Default is 12.

Kwargs:

nrootsint

Number of roots (eigenvalues) requested. Default value is 1.

>>> myadc = adc.UADC(mf).run()
>>> myadcea = adc.UADC(myadc).run()

Saved results

e_eafloat or list of floats
EA energy (eigenvalue). For nroots = 1, it is a single float number. If nroots > 1, it is a list of floats for the lowest nroots eigenvalues.

v_iparray
Eigenvectors for each EA transition.

p_eafloat
Spectroscopic amplitudes for each EA transition.

analyze()#

analyze_eigenvector()#

analyze_spec_factor()#

compute_dyson_mo()#

gen_matvec(imds=None, eris=None)[source]#

get_diag(M_ab=None, eris=None)#

get_imds(eris=None)#

get_init_guess(nroots=1, diag=None, ascending=True)[source]#

get_properties(nroots=1)#

get_trans_moments()#

kernel(nroots=1, guess=None, eris=None, verbose=None)#: Kernel function is the main driver of a method. Every method should define the kernel function as the entry of the calculation. Note the return value of kernel function is not strictly defined. It can be anything related to the method (such as the energy, the wave-function, the DFT mesh grids etc.).

matvec(M_ab=None, eris=None)#

pyscf.adc.uadc_ea.analyze(myadc)[source]#

pyscf.adc.uadc_ea.analyze_eigenvector(adc)[source]#

pyscf.adc.uadc_ea.analyze_spec_factor(adc)[source]#

pyscf.adc.uadc_ea.compute_dyson_mo(myadc)[source]#

pyscf.adc.uadc_ea.contract_r_vvvv(myadc, r2, vvvv_d)[source]#

pyscf.adc.uadc_ea.contract_r_vvvv_antisym(myadc, r2, vvvv_d)[source]#

pyscf.adc.uadc_ea.get_diag(adc, M_ab=None, eris=None)[source]#

pyscf.adc.uadc_ea.get_imds(adc, eris=None)[source]#

pyscf.adc.uadc_ea.get_properties(adc, nroots=1)[source]#

pyscf.adc.uadc_ea.get_trans_moments(adc)[source]#

pyscf.adc.uadc_ea.get_trans_moments_orbital(adc, orb, spin='alpha')[source]#

pyscf.adc.uadc_ea.matvec(adc, M_ab=None, eris=None)[source]#

pyscf.adc.uadc_ip module#

Unrestricted algebraic diagrammatic construction

class pyscf.adc.uadc_ip.UADCIP(adc)[source]#

Bases: UADC

unrestricted ADC for IP energies and spectroscopic amplitudes

Attributes:

verboseint: Print level. Default value equals to Mole.verbose
max_memoryfloat or int: Allowed memory in MB. Default value equals to Mole.max_memory
incore_completebool: Avoid all I/O. Default is False.
methodstring: nth-order ADC method. Options are : ADC(2), ADC(2)-X, ADC(3). Default is ADC(2).
conv_tolfloat: Convergence threshold for Davidson iterations. Default is 1e-12.
max_cycleint: Number of Davidson iterations. Default is 50.
max_spaceint: Space size to hold trial vectors for Davidson iterative diagonalization. Default is 12.

Kwargs:

nrootsint

Number of roots (eigenvalues) requested. Default value is 1.

>>> myadc = adc.UADC(mf).run()
>>> myadcip = adc.UADC(myadc).run()

Saved results

e_ipfloat or list of floats
IP energy (eigenvalue). For nroots = 1, it is a single float number. If nroots > 1, it is a list of floats for the lowest nroots eigenvalues.

v_iparray
Eigenvectors for each IP transition.

p_ipfloat
Spectroscopic amplitudes for each IP transition.

analyze()#

analyze_eigenvector()#

analyze_spec_factor()#

compute_dyson_mo()#

gen_matvec(imds=None, eris=None)[source]#

get_diag(M_ij=None, eris=None)#

get_imds(eris=None)#

get_init_guess(nroots=1, diag=None, ascending=True)[source]#

get_properties(nroots=1)#

get_trans_moments()#

kernel(nroots=1, guess=None, eris=None, verbose=None)#: Kernel function is the main driver of a method. Every method should define the kernel function as the entry of the calculation. Note the return value of kernel function is not strictly defined. It can be anything related to the method (such as the energy, the wave-function, the DFT mesh grids etc.).

make_rdm1()#

matvec(M_ij=None, eris=None)#

pyscf.adc.uadc_ip.analyze(myadc)[source]#

pyscf.adc.uadc_ip.analyze_eigenvector(adc)[source]#

pyscf.adc.uadc_ip.analyze_spec_factor(adc)[source]#

pyscf.adc.uadc_ip.compute_dyson_mo(myadc)[source]#

pyscf.adc.uadc_ip.get_diag(adc, M_ij=None, eris=None)[source]#

pyscf.adc.uadc_ip.get_imds(adc, eris=None)[source]#

pyscf.adc.uadc_ip.get_properties(adc, nroots=1)[source]#

pyscf.adc.uadc_ip.get_trans_moments(adc)[source]#

pyscf.adc.uadc_ip.get_trans_moments_orbital(adc, orb, spin='alpha')[source]#

pyscf.adc.uadc_ip.make_rdm1(adc)[source]#

pyscf.adc.uadc_ip.make_rdm1_eigenvectors(adc, L, R)[source]#

pyscf.adc.uadc_ip.matvec(adc, M_ij=None, eris=None)[source]#

pyscf.adc.uadc_ip_cvs module#

Unrestricted algebraic diagrammatic construction

class pyscf.adc.uadc_ip_cvs.UADCIPCVS(adc)[source]#

Bases: UADC

unrestricted ADC for IP-CVS energies and spectroscopic amplitudes

Attributes:

verboseint: Print level. Default value equals to Mole.verbose
max_memoryfloat or int: Allowed memory in MB. Default value equals to Mole.max_memory
incore_completebool: Avoid all I/O. Default is False.
methodstring: nth-order ADC method. Options are : ADC(2), ADC(2)-X, ADC(3). Default is ADC(2).
conv_tolfloat: Convergence threshold for Davidson iterations. Default is 1e-12.
max_cycleint: Number of Davidson iterations. Default is 50.
max_spaceint: Space size to hold trial vectors for Davidson iterative diagonalization. Default is 12.

Kwargs:

nrootsint

Number of roots (eigenvalues) requested. Default value is 1.

>>> myadc = adc.UADC(mf).run()
>>> myadcip = adc.UADC(myadc).run()

Saved results

e_ipfloat or list of floats
IP energy (eigenvalue). For nroots = 1, it is a single float number. If nroots > 1, it is a list of floats for the lowest nroots eigenvalues.

v_iparray
Eigenvectors for each IP transition.

p_ipfloat
Spectroscopic amplitudes for each IP transition.

analyze()#

analyze_spec_factor()#

compute_dyson_mo()#

gen_matvec(imds=None, eris=None)[source]#

get_diag(M_ij=None, eris=None)#

get_imds(eris=None)#

get_init_guess(nroots=1, diag=None, ascending=True)[source]#

get_properties(nroots=1)#

get_trans_moments()#

kernel(nroots=1, guess=None, eris=None, verbose=None)#: Kernel function is the main driver of a method. Every method should define the kernel function as the entry of the calculation. Note the return value of kernel function is not strictly defined. It can be anything related to the method (such as the energy, the wave-function, the DFT mesh grids etc.).

matvec(M_ij=None, eris=None)#

pyscf.adc.uadc_ip_cvs.analyze(myadc)[source]#

pyscf.adc.uadc_ip_cvs.analyze_spec_factor(adc)[source]#

pyscf.adc.uadc_ip_cvs.compute_dyson_mo(myadc)[source]#

pyscf.adc.uadc_ip_cvs.get_diag(adc, M_ij=None, eris=None)[source]#

pyscf.adc.uadc_ip_cvs.get_imds(adc, eris=None)[source]#

pyscf.adc.uadc_ip_cvs.get_properties(adc, nroots=1)[source]#

pyscf.adc.uadc_ip_cvs.get_trans_moments(adc)[source]#

pyscf.adc.uadc_ip_cvs.get_trans_moments_orbital(adc, orb, spin='alpha')[source]#

pyscf.adc.uadc_ip_cvs.matvec(adc, M_ij=None, eris=None)[source]#

Module contents#

Algebraic Diagrammatic Construction#

pyscf.adc.ADC(mf, frozen=None, mo_coeff=None, mo_occ=None)[source]#

Ground state calculations

Attributes:

verboseint

Print level. Default value equals to Mole.verbose

max_memoryfloat or int

Allowed memory in MB. Default value equals to Mole.max_memory

incore_completebool

Avoid all I/O. Default is False.

methodstring

nth-order ADC method. Options are : ADC(2), ADC(2)-X, ADC(3). Default is ADC(2).

>>> mol = gto.M(atom = 'H 0 0 0; F 0 0 1.1', basis = 'ccpvdz')
>>> mf = scf.RHF(mol).run()
>>> myadc = adc.UADC(mf).run()

Saved results

e_corrfloat
MPn correlation correction

e_totfloat
Total energy (HF + correlation)

t1, t2 :
T amplitudes t1[i,a], t2[i,j,a,b] (i,j in occ, a,b in virt)

pyscf.adc.RADC(mf, frozen=None, mo_coeff=None, mo_occ=None)[source]#

Ground state calculations

Attributes:

verboseint

Print level. Default value equals to Mole.verbose

max_memoryfloat or int

Allowed memory in MB. Default value equals to Mole.max_memory

incore_completebool

Avoid all I/O. Default is False.

methodstring

nth-order ADC method. Options are : ADC(2), ADC(2)-X, ADC(3). Default is ADC(2).

>>> mol = gto.M(atom = 'H 0 0 0; F 0 0 1.1', basis = 'ccpvdz')
>>> mf = scf.RHF(mol).run()
>>> myadc = adc.RADC(mf).run()

Saved results

e_corrfloat
MPn correlation correction

e_totfloat
Total energy (HF + correlation)

t1, t2 :
T amplitudes t1[i,a], t2[i,j,a,b] (i,j in occ, a,b in virt)

pyscf.adc.UADC(mf, frozen=None, mo_coeff=None, mo_occ=None)[source]#

Ground state calculations

Attributes:

verboseint

Print level. Default value equals to Mole.verbose

max_memoryfloat or int

Allowed memory in MB. Default value equals to Mole.max_memory

incore_completebool

Avoid all I/O. Default is False.

methodstring

nth-order ADC method. Options are : ADC(2), ADC(2)-X, ADC(3). Default is ADC(2).

>>> mol = gto.M(atom = 'H 0 0 0; F 0 0 1.1', basis = 'ccpvdz')
>>> mf = scf.RHF(mol).run()
>>> myadc = adc.UADC(mf).run()

Saved results

e_corrfloat
MPn correlation correction

e_totfloat
Total energy (HF + correlation)

t1, t2 :
T amplitudes t1[i,a], t2[i,j,a,b] (i,j in occ, a,b in virt)