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Introduced nxn diagonalization for PT2
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@ -1,4 +1,3 @@
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use bitmasks
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BEGIN_PROVIDER [ double precision, pt2_match_weight, (N_states) ]
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@ -144,6 +143,23 @@ BEGIN_PROVIDER [ double precision, selection_weight, (N_states) ]
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END_PROVIDER
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BEGIN_PROVIDER [ logical, banned_excitation, (mo_num,mo_num) ]
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implicit none
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BEGIN_DOC
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! If true, the excitation is banned in the selection. Useful with local MOs.
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END_DOC
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banned_excitation = .False.
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integer :: i,j
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double precision :: buffer(mo_num)
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do j=1,mo_num
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call get_mo_two_e_integrals_exch_ii(j,j,mo_num,buffer,mo_integrals_map)
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buffer = dabs(buffer)
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do i=1,mo_num
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banned_excitation(i,j) = buffer(i) < 1.d-15
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enddo
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enddo
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END_PROVIDER
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subroutine get_mask_phase(det1, pm, Nint)
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use bitmasks
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@ -288,6 +304,7 @@ subroutine select_singles_and_doubles(i_generator,hole_mask,particle_mask,fock_d
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PROVIDE psi_bilinear_matrix_rows psi_det_sorted_order psi_bilinear_matrix_order
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PROVIDE psi_bilinear_matrix_transp_rows_loc psi_bilinear_matrix_transp_columns
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PROVIDE psi_bilinear_matrix_transp_order psi_selectors_coef_transp
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PROVIDE banned_excitation
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monoAdo = .true.
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monoBdo = .true.
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@ -607,7 +624,8 @@ subroutine select_singles_and_doubles(i_generator,hole_mask,particle_mask,fock_d
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h2 = hole_list(i2,s2)
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call apply_hole(pmask, s2,h2, mask, ok, N_int)
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banned = .false.
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banned(:,:,1) = banned_excitation(:,:)
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banned(:,:,2) = banned_excitation(:,:)
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do j=1,mo_num
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bannedOrb(j, 1) = .true.
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bannedOrb(j, 2) = .true.
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@ -674,7 +692,7 @@ subroutine fill_buffer_double(i_generator, sp, h1, h2, bannedOrb, banned, fock_d
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logical :: ok
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integer :: s1, s2, p1, p2, ib, j, istate, jstate
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integer(bit_kind) :: mask(N_int, 2), det(N_int, 2)
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double precision :: e_pert(N_states), coef(N_states), X(N_states)
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double precision :: e_pert(N_states), coef(N_states)
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double precision :: delta_E, val, Hii, w, tmp, alpha_h_psi
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double precision, external :: diag_H_mat_elem_fock
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double precision :: E_shift
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@ -769,10 +787,16 @@ subroutine fill_buffer_double(i_generator, sp, h1, h2, bannedOrb, banned, fock_d
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! call occ_pattern_of_det(det,occ,N_int)
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! call occ_pattern_to_dets_size(occ,n,elec_alpha_num,N_int)
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e_pert = 0.d0
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coef = 0.d0
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logical :: do_diag
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do_diag = .False.
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do istate=1,N_states
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delta_E = E0(istate) - Hii + E_shift
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alpha_h_psi = mat(istate, p1, p2)
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if (alpha_h_psi == 0.d0) cycle
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val = alpha_h_psi + alpha_h_psi
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tmp = dsqrt(delta_E * delta_E + val * val)
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if (delta_E < 0.d0) then
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@ -784,13 +808,38 @@ subroutine fill_buffer_double(i_generator, sp, h1, h2, bannedOrb, banned, fock_d
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else
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coef(istate) = alpha_h_psi / delta_E
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endif
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if (e_pert(istate) < 0.d0) then
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X(istate) = -dsqrt(-e_pert(istate))
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else
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X(istate) = dsqrt(e_pert(istate))
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endif
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enddo
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do_diag = maxval(dabs(coef)) > 0.001d0
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double precision :: eigvalues(N_states+1)
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double precision :: work(1+6*(N_states+1)+2*(N_states+1)**2)
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integer :: iwork(3+5*(N_states+1)), info, k ,n
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if (do_diag) then
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double precision :: pt2_matrix(N_states+1,N_states+1)
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pt2_matrix(N_states+1,N_states+1) = Hii+E_shift
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do istate=1,N_states
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pt2_matrix(:,istate) = 0.d0
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pt2_matrix(istate,istate) = E0(istate)
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pt2_matrix(istate,N_states+1) = mat(istate,p1,p2)
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pt2_matrix(N_states+1,istate) = mat(istate,p1,p2)
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enddo
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call DSYEVD( 'V', 'U', N_states+1, pt2_matrix, N_states+1, eigvalues, &
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work, size(work), iwork, size(iwork), info )
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if (info /= 0) then
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print *, 'error in '//irp_here
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stop -1
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endif
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pt2_matrix = dabs(pt2_matrix)
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iwork = maxloc(pt2_matrix,1)
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do k=1,N_states
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e_pert(iwork(k)) = eigvalues(k) - E0(iwork(k))
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enddo
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endif
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! ! Gram-Schmidt using input overlap matrix
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! do istate=1,N_states
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! do jstate=1,istate-1
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@ -835,25 +884,25 @@ subroutine fill_buffer_double(i_generator, sp, h1, h2, bannedOrb, banned, fock_d
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case(5)
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! Variance selection
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w = w - alpha_h_psi * alpha_h_psi * s_weight(istate,istate)
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do jstate=1,N_states
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if (istate == jstate) cycle
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w = w + alpha_h_psi*mat(jstate,p1,p2) * s_weight(istate,jstate)
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enddo
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! do jstate=1,N_states
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! if (istate == jstate) cycle
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! w = w + dabs(alpha_h_psi*mat(jstate,p1,p2)) * s_weight(istate,jstate)
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! enddo
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case(6)
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w = w - coef(istate) * coef(istate) * s_weight(istate,istate)
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do jstate=1,N_states
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if (istate == jstate) cycle
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w = w + coef(istate)*coef(jstate) * s_weight(istate,jstate)
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enddo
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! do jstate=1,N_states
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! if (istate == jstate) cycle
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! w = w + dabs(coef(istate)*coef(jstate)) * s_weight(istate,jstate)
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! enddo
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case default
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! Energy selection
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w = w + e_pert(istate) * s_weight(istate,istate)
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do jstate=1,N_states
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if (istate == jstate) cycle
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w = w - dabs(X(istate))*X(jstate) * s_weight(istate,jstate)
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enddo
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! do jstate=1,N_states
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! if (istate == jstate) cycle
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! w = w + dabs(X(istate)*X(jstate)) * s_weight(istate,jstate)
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! enddo
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end select
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end do
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@ -19,7 +19,7 @@ subroutine svd(A,LDA,U,LDU,D,Vt,LDVt,m,n)
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double precision,allocatable :: A_tmp(:,:)
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allocate (A_tmp(LDA,n))
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A_tmp = A
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A_tmp(:,:) = A(:,:)
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! Find optimal size for temp arrays
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allocate(work(1))
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