mirror of
https://github.com/QuantumPackage/qp2.git
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84 lines
3.5 KiB
Fortran
84 lines
3.5 KiB
Fortran
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BEGIN_PROVIDER[double precision, aos_vc_alpha_LDA_w, (ao_num,n_points_final_grid,N_states)]
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&BEGIN_PROVIDER[double precision, aos_vc_beta_LDA_w, (ao_num,n_points_final_grid,N_states)]
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&BEGIN_PROVIDER[double precision, aos_vx_alpha_LDA_w, (ao_num,n_points_final_grid,N_states)]
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&BEGIN_PROVIDER[double precision, aos_vx_beta_LDA_w, (ao_num,n_points_final_grid,N_states)]
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implicit none
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BEGIN_DOC
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! aos_vxc_alpha_LDA_w(j,i) = ao_i(r_j) * (v^x_alpha(r_j) + v^c_alpha(r_j)) * W(r_j)
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END_DOC
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integer :: istate,i,j
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double precision :: r(3)
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double precision :: mu,weight
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double precision :: e_c,vc_a,vc_b,e_x,vx_a,vx_b
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double precision, allocatable :: rhoa(:),rhob(:)
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double precision :: mu_local
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mu_local = 1.d-9
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allocate(rhoa(N_states), rhob(N_states))
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do istate = 1, N_states
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do i = 1, n_points_final_grid
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r(1) = final_grid_points(1,i)
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r(2) = final_grid_points(2,i)
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r(3) = final_grid_points(3,i)
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weight = final_weight_at_r_vector(i)
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rhoa(istate) = one_e_dm_alpha_at_r(i,istate)
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rhob(istate) = one_e_dm_beta_at_r(i,istate)
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call ec_LDA_sr(mu_local,rhoa(istate),rhob(istate),e_c,vc_a,vc_b)
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call ex_LDA_sr(mu_local,rhoa(istate),rhob(istate),e_x,vx_a,vx_b)
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do j =1, ao_num
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aos_vc_alpha_LDA_w(j,i,istate) = vc_a * aos_in_r_array(j,i)*weight
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aos_vc_beta_LDA_w(j,i,istate) = vc_b * aos_in_r_array(j,i)*weight
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aos_vx_alpha_LDA_w(j,i,istate) = vx_a * aos_in_r_array(j,i)*weight
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aos_vx_beta_LDA_w(j,i,istate) = vx_b * aos_in_r_array(j,i)*weight
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enddo
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enddo
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enddo
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END_PROVIDER
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BEGIN_PROVIDER [double precision, potential_x_alpha_ao_LDA,(ao_num,ao_num,N_states)]
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&BEGIN_PROVIDER [double precision, potential_x_beta_ao_LDA,(ao_num,ao_num,N_states)]
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implicit none
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BEGIN_DOC
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! short range exchange alpha/beta potentials with LDA functional on the |AO| basis
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END_DOC
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! Second dimension is given as ao_num * N_states so that Lapack does the loop over N_states.
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integer :: istate
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do istate = 1, N_states
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call dgemm('N','T',ao_num,ao_num,n_points_final_grid,1.d0, &
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aos_in_r_array,size(aos_in_r_array,1), &
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aos_vx_alpha_LDA_w(1,1,istate),size(aos_vx_alpha_LDA_w,1),0.d0,&
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potential_x_alpha_ao_LDA(1,1,istate),size(potential_x_alpha_ao_LDA,1))
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call dgemm('N','T',ao_num,ao_num,n_points_final_grid,1.d0, &
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aos_in_r_array,size(aos_in_r_array,1), &
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aos_vx_beta_LDA_w(1,1,istate),size(aos_vx_beta_LDA_w,1),0.d0,&
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potential_x_beta_ao_LDA(1,1,istate),size(potential_x_beta_ao_LDA,1))
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enddo
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END_PROVIDER
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BEGIN_PROVIDER [double precision, potential_c_alpha_ao_LDA,(ao_num,ao_num,N_states)]
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&BEGIN_PROVIDER [double precision, potential_c_beta_ao_LDA,(ao_num,ao_num,N_states)]
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implicit none
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BEGIN_DOC
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! short range correlation alpha/beta potentials with LDA functional on the |AO| basis
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END_DOC
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! Second dimension is given as ao_num * N_states so that Lapack does the loop over N_states.
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integer :: istate
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do istate = 1, N_states
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call dgemm('N','T',ao_num,ao_num,n_points_final_grid,1.d0, &
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aos_in_r_array,size(aos_in_r_array,1), &
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aos_vc_alpha_LDA_w(1,1,istate),size(aos_vc_alpha_LDA_w,1),0.d0,&
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potential_c_alpha_ao_LDA(1,1,istate),size(potential_c_alpha_ao_LDA,1))
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call dgemm('N','T',ao_num,ao_num,n_points_final_grid,1.d0, &
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aos_in_r_array,size(aos_in_r_array,1), &
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aos_vc_beta_LDA_w(1,1,istate),size(aos_vc_beta_LDA_w,1),0.d0,&
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potential_c_beta_ao_LDA(1,1,istate),size(potential_c_beta_ao_LDA,1))
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enddo
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END_PROVIDER
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