2023-02-06 18:17:56 +01:00
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2023-05-07 12:44:59 +02:00
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! ---
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BEGIN_PROVIDER [ double precision, int2_grad1u2_grad2u2, (ao_num, ao_num, n_points_final_grid)]
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BEGIN_DOC
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!
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2024-01-17 19:23:24 +01:00
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! \frac{1}{4} x int dr2 phi_i(r2) phi_j(r2) [1 - erf(mu r12)]^2
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2023-05-07 12:44:59 +02:00
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!
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END_DOC
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implicit none
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integer :: i, j, ipoint, i_fit
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double precision :: r(3), expo_fit, coef_fit
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double precision :: tmp
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double precision :: wall0, wall1
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double precision, external :: overlap_gauss_r12_ao
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print*, ' providing int2_grad1u2_grad2u2 ...'
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call wall_time(wall0)
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2024-01-15 12:02:38 +01:00
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provide mu_erf
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provide final_grid_points
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2023-05-07 12:44:59 +02:00
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int2_grad1u2_grad2u2 = 0.d0
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2023-05-07 15:07:51 +02:00
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!$OMP PARALLEL DEFAULT (NONE) &
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!$OMP PRIVATE (ipoint, i, j, i_fit, r, coef_fit, expo_fit, tmp) &
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!$OMP SHARED (n_points_final_grid, ao_num, final_grid_points, ng_fit_jast, &
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!$OMP expo_gauss_1_erf_x_2, coef_gauss_1_erf_x_2,int2_grad1u2_grad2u2)
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!$OMP DO
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2023-05-07 12:44:59 +02:00
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do ipoint = 1, n_points_final_grid
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r(1) = final_grid_points(1,ipoint)
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r(2) = final_grid_points(2,ipoint)
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r(3) = final_grid_points(3,ipoint)
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do i = 1, ao_num
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do j = i, ao_num
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tmp = 0.d0
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do i_fit = 1, ng_fit_jast
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expo_fit = expo_gauss_1_erf_x_2(i_fit)
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coef_fit = coef_gauss_1_erf_x_2(i_fit)
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2024-01-17 19:23:24 +01:00
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tmp += 0.25d0 * coef_fit * overlap_gauss_r12_ao(r, expo_fit, i, j)
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2023-05-07 12:44:59 +02:00
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enddo
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int2_grad1u2_grad2u2(j,i,ipoint) = tmp
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enddo
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enddo
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enddo
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2023-05-07 15:07:51 +02:00
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!$OMP END DO
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!$OMP END PARALLEL
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2023-05-07 12:44:59 +02:00
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do ipoint = 1, n_points_final_grid
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do i = 2, ao_num
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do j = 1, i-1
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int2_grad1u2_grad2u2(j,i,ipoint) = int2_grad1u2_grad2u2(i,j,ipoint)
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enddo
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enddo
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enddo
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call wall_time(wall1)
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2024-01-15 12:02:38 +01:00
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print*, ' wall time for int2_grad1u2_grad2u2 (min) = ', (wall1 - wall0) / 60.d0
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2023-05-07 12:44:59 +02:00
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END_PROVIDER
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2023-02-06 18:17:56 +01:00
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! ---
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2024-01-15 12:02:38 +01:00
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BEGIN_PROVIDER [double precision, int2_grad1u2_grad2u2_env2, (ao_num, ao_num, n_points_final_grid)]
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2023-02-06 18:17:56 +01:00
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BEGIN_DOC
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!
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2024-01-15 12:02:38 +01:00
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! -\frac{1}{4} x int dr2 phi_i(r2) phi_j(r2) 1s_env(r2)^2 [1 - erf(mu r12)]^2
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2023-02-06 18:17:56 +01:00
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!
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END_DOC
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implicit none
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integer :: i, j, ipoint, i_1s, i_fit
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double precision :: r(3), int_fit, expo_fit, coef_fit
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double precision :: coef, beta, B_center(3)
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double precision :: tmp
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double precision :: wall0, wall1
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double precision, external :: overlap_gauss_r12_ao
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double precision, external :: overlap_gauss_r12_ao_with1s
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2024-01-15 12:02:38 +01:00
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print*, ' providing int2_grad1u2_grad2u2_env2 ...'
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2023-02-06 18:17:56 +01:00
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call wall_time(wall0)
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2024-01-15 12:02:38 +01:00
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provide mu_erf
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provide final_grid_points
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2023-02-06 18:17:56 +01:00
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2024-01-15 12:02:38 +01:00
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int2_grad1u2_grad2u2_env2 = 0.d0
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2023-02-06 18:17:56 +01:00
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2024-01-17 19:23:24 +01:00
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!$OMP PARALLEL DEFAULT (NONE) &
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!$OMP PRIVATE (ipoint, i, j, i_1s, i_fit, r, coef, beta, B_center, &
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!$OMP coef_fit, expo_fit, int_fit, tmp) &
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2024-01-15 12:02:38 +01:00
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!$OMP SHARED (n_points_final_grid, ao_num, List_env1s_square_size, &
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2024-01-17 19:23:24 +01:00
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!$OMP final_grid_points, ng_fit_jast, &
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!$OMP expo_gauss_1_erf_x_2, coef_gauss_1_erf_x_2, &
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!$OMP List_env1s_square_coef, List_env1s_square_expo, &
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2024-01-15 12:02:38 +01:00
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!$OMP List_env1s_square_cent, int2_grad1u2_grad2u2_env2)
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2023-05-07 15:07:51 +02:00
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!$OMP DO
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2023-02-06 18:17:56 +01:00
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do ipoint = 1, n_points_final_grid
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r(1) = final_grid_points(1,ipoint)
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r(2) = final_grid_points(2,ipoint)
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r(3) = final_grid_points(3,ipoint)
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do i = 1, ao_num
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do j = i, ao_num
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tmp = 0.d0
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do i_fit = 1, ng_fit_jast
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expo_fit = expo_gauss_1_erf_x_2(i_fit)
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coef_fit = coef_gauss_1_erf_x_2(i_fit)
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! ---
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int_fit = overlap_gauss_r12_ao(r, expo_fit, i, j)
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tmp += -0.25d0 * coef_fit * int_fit
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2023-05-07 15:07:51 +02:00
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! if(dabs(coef_fit*int_fit) .lt. 1d-12) cycle
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2023-02-06 18:17:56 +01:00
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! ---
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2024-01-15 12:02:38 +01:00
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do i_1s = 2, List_env1s_square_size
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2023-02-06 18:17:56 +01:00
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2024-01-15 12:02:38 +01:00
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coef = List_env1s_square_coef (i_1s)
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2023-07-03 00:47:55 +02:00
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if(dabs(coef) .lt. 1d-15) cycle ! beta = 0.0
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2024-01-15 12:02:38 +01:00
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beta = List_env1s_square_expo (i_1s)
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B_center(1) = List_env1s_square_cent(1,i_1s)
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B_center(2) = List_env1s_square_cent(2,i_1s)
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B_center(3) = List_env1s_square_cent(3,i_1s)
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2023-02-06 18:17:56 +01:00
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int_fit = overlap_gauss_r12_ao_with1s(B_center, beta, r, expo_fit, i, j)
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tmp += -0.25d0 * coef * coef_fit * int_fit
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enddo
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! ---
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enddo
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2024-01-15 12:02:38 +01:00
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int2_grad1u2_grad2u2_env2(j,i,ipoint) = tmp
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2023-02-06 18:17:56 +01:00
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enddo
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enddo
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enddo
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2023-05-07 15:07:51 +02:00
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!$OMP END DO
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!$OMP END PARALLEL
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2023-02-06 18:17:56 +01:00
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do ipoint = 1, n_points_final_grid
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do i = 2, ao_num
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do j = 1, i-1
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2024-01-15 12:02:38 +01:00
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int2_grad1u2_grad2u2_env2(j,i,ipoint) = int2_grad1u2_grad2u2_env2(i,j,ipoint)
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2023-02-06 18:17:56 +01:00
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enddo
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enddo
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enddo
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call wall_time(wall1)
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2024-01-15 12:02:38 +01:00
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print*, ' wall time for int2_grad1u2_grad2u2_env2 (min) =', (wall1 - wall0) / 60.d0
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2023-02-06 18:17:56 +01:00
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END_PROVIDER
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! ---
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2024-01-15 12:02:38 +01:00
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BEGIN_PROVIDER [double precision, int2_u2_env2, (ao_num, ao_num, n_points_final_grid)]
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2023-02-06 18:17:56 +01:00
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BEGIN_DOC
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!
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2024-01-15 12:02:38 +01:00
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! int dr2 phi_i(r2) phi_j(r2) 1s_env(r2)^2 [u_12^mu]^2
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2023-02-06 18:17:56 +01:00
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!
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END_DOC
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implicit none
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integer :: i, j, ipoint, i_1s, i_fit
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double precision :: r(3), int_fit, expo_fit, coef_fit
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double precision :: coef, beta, B_center(3), tmp
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double precision :: wall0, wall1
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double precision, external :: overlap_gauss_r12_ao
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double precision, external :: overlap_gauss_r12_ao_with1s
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2024-01-15 12:02:38 +01:00
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print*, ' providing int2_u2_env2 ...'
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2023-02-06 18:17:56 +01:00
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call wall_time(wall0)
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2024-01-15 12:02:38 +01:00
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provide mu_erf
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provide final_grid_points
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2023-02-06 18:17:56 +01:00
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2024-01-15 12:02:38 +01:00
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int2_u2_env2 = 0.d0
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2023-02-06 18:17:56 +01:00
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2024-01-17 19:23:24 +01:00
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!$OMP PARALLEL DEFAULT (NONE) &
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!$OMP PRIVATE (ipoint, i, j, i_1s, i_fit, r, coef, beta, B_center, &
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!$OMP coef_fit, expo_fit, int_fit, tmp) &
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2024-01-15 12:02:38 +01:00
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!$OMP SHARED (n_points_final_grid, ao_num, List_env1s_square_size, &
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2024-01-17 19:23:24 +01:00
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!$OMP final_grid_points, ng_fit_jast, &
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!$OMP expo_gauss_j_mu_x_2, coef_gauss_j_mu_x_2, &
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!$OMP List_env1s_square_coef, List_env1s_square_expo, &
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2024-01-15 12:02:38 +01:00
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!$OMP List_env1s_square_cent, int2_u2_env2)
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2023-05-07 15:07:51 +02:00
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!$OMP DO
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2023-02-06 18:17:56 +01:00
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do ipoint = 1, n_points_final_grid
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r(1) = final_grid_points(1,ipoint)
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r(2) = final_grid_points(2,ipoint)
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r(3) = final_grid_points(3,ipoint)
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do i = 1, ao_num
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do j = i, ao_num
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tmp = 0.d0
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do i_fit = 1, ng_fit_jast
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expo_fit = expo_gauss_j_mu_x_2(i_fit)
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coef_fit = coef_gauss_j_mu_x_2(i_fit)
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! ---
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int_fit = overlap_gauss_r12_ao(r, expo_fit, i, j)
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tmp += coef_fit * int_fit
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2023-05-07 15:07:51 +02:00
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! if(dabs(coef_fit*int_fit) .lt. 1d-12) cycle
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2023-02-06 18:17:56 +01:00
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! ---
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2024-01-15 12:02:38 +01:00
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do i_1s = 2, List_env1s_square_size
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2023-02-06 18:17:56 +01:00
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2024-01-15 12:02:38 +01:00
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coef = List_env1s_square_coef (i_1s)
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2023-07-03 00:47:55 +02:00
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if(dabs(coef) .lt. 1d-15) cycle ! beta = 0.0
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2024-01-15 12:02:38 +01:00
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beta = List_env1s_square_expo (i_1s)
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B_center(1) = List_env1s_square_cent(1,i_1s)
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B_center(2) = List_env1s_square_cent(2,i_1s)
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B_center(3) = List_env1s_square_cent(3,i_1s)
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2023-02-06 18:17:56 +01:00
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int_fit = overlap_gauss_r12_ao_with1s(B_center, beta, r, expo_fit, i, j)
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tmp += coef * coef_fit * int_fit
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enddo
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! ---
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enddo
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2024-01-15 12:02:38 +01:00
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int2_u2_env2(j,i,ipoint) = tmp
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2023-02-06 18:17:56 +01:00
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enddo
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enddo
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enddo
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2023-05-07 15:07:51 +02:00
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!$OMP END DO
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!$OMP END PARALLEL
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2023-02-06 18:17:56 +01:00
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do ipoint = 1, n_points_final_grid
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do i = 2, ao_num
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do j = 1, i-1
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2024-01-15 12:02:38 +01:00
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int2_u2_env2(j,i,ipoint) = int2_u2_env2(i,j,ipoint)
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2023-02-06 18:17:56 +01:00
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enddo
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enddo
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enddo
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call wall_time(wall1)
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2024-01-15 12:02:38 +01:00
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print*, ' wall time for int2_u2_env2 (min) = ', (wall1 - wall0) / 60.d0
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2023-02-06 18:17:56 +01:00
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END_PROVIDER
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! ---
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2024-01-15 12:02:38 +01:00
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BEGIN_PROVIDER [double precision, int2_u_grad1u_x_env2, (ao_num, ao_num, n_points_final_grid, 3)]
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2023-02-06 18:17:56 +01:00
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BEGIN_DOC
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!
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2024-01-15 12:02:38 +01:00
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! int dr2 phi_i(r2) phi_j(r2) 1s_env(r2)^2 u_12^mu [\grad_1 u_12^mu] r2
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2023-02-06 18:17:56 +01:00
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!
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END_DOC
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implicit none
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integer :: i, j, ipoint, i_1s, i_fit
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double precision :: r(3), int_fit(3), expo_fit, coef_fit
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double precision :: coef, beta, B_center(3), dist
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double precision :: alpha_1s, alpha_1s_inv, centr_1s(3), expo_coef_1s, coef_tmp
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double precision :: tmp_x, tmp_y, tmp_z
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double precision :: wall0, wall1
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2024-01-15 12:02:38 +01:00
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print*, ' providing int2_u_grad1u_x_env2 ...'
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2023-02-06 18:17:56 +01:00
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call wall_time(wall0)
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2024-01-15 12:02:38 +01:00
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provide mu_erf
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provide final_grid_points
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2023-02-06 18:17:56 +01:00
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2024-01-15 12:02:38 +01:00
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int2_u_grad1u_x_env2 = 0.d0
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2023-02-06 18:17:56 +01:00
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2024-01-17 19:23:24 +01:00
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!$OMP PARALLEL DEFAULT (NONE) &
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!$OMP PRIVATE (ipoint, i, j, i_1s, i_fit, r, coef, beta, B_center, &
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!$OMP coef_fit, expo_fit, int_fit, alpha_1s, dist, &
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!$OMP alpha_1s_inv, centr_1s, expo_coef_1s, coef_tmp, &
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!$OMP tmp_x, tmp_y, tmp_z) &
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2024-01-15 12:02:38 +01:00
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!$OMP SHARED (n_points_final_grid, ao_num, List_env1s_square_size, &
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2024-01-17 19:23:24 +01:00
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!$OMP final_grid_points, ng_fit_jast, &
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!$OMP expo_gauss_j_mu_1_erf, coef_gauss_j_mu_1_erf, &
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!$OMP List_env1s_square_coef, List_env1s_square_expo, &
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2024-01-15 12:02:38 +01:00
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!$OMP List_env1s_square_cent, int2_u_grad1u_x_env2)
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2023-02-06 18:17:56 +01:00
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!$OMP DO
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do ipoint = 1, n_points_final_grid
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r(1) = final_grid_points(1,ipoint)
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r(2) = final_grid_points(2,ipoint)
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r(3) = final_grid_points(3,ipoint)
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do i = 1, ao_num
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do j = i, ao_num
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tmp_x = 0.d0
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tmp_y = 0.d0
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tmp_z = 0.d0
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do i_fit = 1, ng_fit_jast
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expo_fit = expo_gauss_j_mu_1_erf(i_fit)
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coef_fit = coef_gauss_j_mu_1_erf(i_fit)
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! ---
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call NAI_pol_x_mult_erf_ao_with1s(i, j, expo_fit, r, 1.d+9, r, int_fit)
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tmp_x += coef_fit * int_fit(1)
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tmp_y += coef_fit * int_fit(2)
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tmp_z += coef_fit * int_fit(3)
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! if( dabs(coef_fit)*(dabs(int_fit(1)) + dabs(int_fit(2)) + dabs(int_fit(3))) .lt. 3d-10 ) cycle
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! ---
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2024-01-15 12:02:38 +01:00
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do i_1s = 2, List_env1s_square_size
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2023-02-06 18:17:56 +01:00
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2024-01-15 12:02:38 +01:00
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coef = List_env1s_square_coef (i_1s)
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2023-07-03 00:47:55 +02:00
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if(dabs(coef) .lt. 1d-15) cycle ! beta = 0.0
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2024-01-15 12:02:38 +01:00
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beta = List_env1s_square_expo (i_1s)
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B_center(1) = List_env1s_square_cent(1,i_1s)
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B_center(2) = List_env1s_square_cent(2,i_1s)
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B_center(3) = List_env1s_square_cent(3,i_1s)
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2023-02-06 18:17:56 +01:00
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dist = (B_center(1) - r(1)) * (B_center(1) - r(1)) &
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+ (B_center(2) - r(2)) * (B_center(2) - r(2)) &
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+ (B_center(3) - r(3)) * (B_center(3) - r(3))
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alpha_1s = beta + expo_fit
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alpha_1s_inv = 1.d0 / alpha_1s
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centr_1s(1) = alpha_1s_inv * (beta * B_center(1) + expo_fit * r(1))
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centr_1s(2) = alpha_1s_inv * (beta * B_center(2) + expo_fit * r(2))
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centr_1s(3) = alpha_1s_inv * (beta * B_center(3) + expo_fit * r(3))
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expo_coef_1s = beta * expo_fit * alpha_1s_inv * dist
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coef_tmp = coef * coef_fit * dexp(-expo_coef_1s)
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! if(dabs(coef_tmp) .lt. 1d-12) cycle
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call NAI_pol_x_mult_erf_ao_with1s(i, j, alpha_1s, centr_1s, 1.d+9, r, int_fit)
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tmp_x += coef_tmp * int_fit(1)
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tmp_y += coef_tmp * int_fit(2)
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tmp_z += coef_tmp * int_fit(3)
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enddo
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! ---
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enddo
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2024-01-15 12:02:38 +01:00
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int2_u_grad1u_x_env2(j,i,ipoint,1) = tmp_x
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int2_u_grad1u_x_env2(j,i,ipoint,2) = tmp_y
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int2_u_grad1u_x_env2(j,i,ipoint,3) = tmp_z
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2023-02-06 18:17:56 +01:00
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enddo
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enddo
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enddo
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!$OMP END DO
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!$OMP END PARALLEL
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do ipoint = 1, n_points_final_grid
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do i = 2, ao_num
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do j = 1, i-1
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2024-01-15 12:02:38 +01:00
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int2_u_grad1u_x_env2(j,i,ipoint,1) = int2_u_grad1u_x_env2(i,j,ipoint,1)
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int2_u_grad1u_x_env2(j,i,ipoint,2) = int2_u_grad1u_x_env2(i,j,ipoint,2)
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int2_u_grad1u_x_env2(j,i,ipoint,3) = int2_u_grad1u_x_env2(i,j,ipoint,3)
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2023-02-06 18:17:56 +01:00
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enddo
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enddo
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enddo
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call wall_time(wall1)
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2024-01-15 12:02:38 +01:00
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print*, ' wall time for int2_u_grad1u_x_env2 (min) = ', (wall1 - wall0) / 60.d0
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2023-02-06 18:17:56 +01:00
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END_PROVIDER
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! ---
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|
2024-01-15 12:02:38 +01:00
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BEGIN_PROVIDER [ double precision, int2_u_grad1u_env2, (ao_num, ao_num, n_points_final_grid)]
|
2023-02-06 18:17:56 +01:00
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|
BEGIN_DOC
|
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|
|
!
|
2024-01-15 12:02:38 +01:00
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|
! int dr2 phi_i(r2) phi_j(r2) 1s_env(r2)^2 u_12^mu [\grad_1 u_12^mu]
|
2023-02-06 18:17:56 +01:00
|
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|
!
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|
END_DOC
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|
implicit none
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|
|
integer :: i, j, ipoint, i_1s, i_fit
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double precision :: r(3), int_fit, expo_fit, coef_fit, coef_tmp
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|
double precision :: coef, beta, B_center(3), dist
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|
double precision :: alpha_1s, alpha_1s_inv, centr_1s(3), expo_coef_1s, tmp
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|
double precision :: wall0, wall1
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|
double precision, external :: NAI_pol_mult_erf_ao_with1s
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|
2024-01-15 12:02:38 +01:00
|
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|
print*, ' providing int2_u_grad1u_env2 ...'
|
2023-02-06 18:17:56 +01:00
|
|
|
call wall_time(wall0)
|
|
|
|
|
2024-01-15 12:02:38 +01:00
|
|
|
provide mu_erf
|
|
|
|
provide final_grid_points
|
2023-02-06 18:17:56 +01:00
|
|
|
|
2024-01-15 12:02:38 +01:00
|
|
|
int2_u_grad1u_env2 = 0.d0
|
2023-02-06 18:17:56 +01:00
|
|
|
|
2024-01-17 19:23:24 +01:00
|
|
|
!$OMP PARALLEL DEFAULT (NONE) &
|
|
|
|
!$OMP PRIVATE (ipoint, i, j, i_1s, i_fit, r, coef, beta, B_center, &
|
|
|
|
!$OMP coef_fit, expo_fit, int_fit, tmp, alpha_1s, dist, &
|
|
|
|
!$OMP alpha_1s_inv, centr_1s, expo_coef_1s, coef_tmp) &
|
2024-01-15 12:02:38 +01:00
|
|
|
!$OMP SHARED (n_points_final_grid, ao_num, List_env1s_square_size, &
|
2024-01-17 19:23:24 +01:00
|
|
|
!$OMP final_grid_points, ng_fit_jast, &
|
|
|
|
!$OMP expo_gauss_j_mu_1_erf, coef_gauss_j_mu_1_erf, &
|
|
|
|
!$OMP List_env1s_square_coef, List_env1s_square_expo, &
|
2024-01-15 12:02:38 +01:00
|
|
|
!$OMP List_env1s_square_cent, int2_u_grad1u_env2)
|
2023-02-06 18:17:56 +01:00
|
|
|
!$OMP DO
|
|
|
|
do ipoint = 1, n_points_final_grid
|
|
|
|
do i = 1, ao_num
|
|
|
|
do j = i, ao_num
|
|
|
|
r(1) = final_grid_points(1,ipoint)
|
|
|
|
r(2) = final_grid_points(2,ipoint)
|
|
|
|
r(3) = final_grid_points(3,ipoint)
|
|
|
|
|
|
|
|
tmp = 0.d0
|
|
|
|
do i_fit = 1, ng_fit_jast
|
|
|
|
|
|
|
|
expo_fit = expo_gauss_j_mu_1_erf(i_fit)
|
|
|
|
coef_fit = coef_gauss_j_mu_1_erf(i_fit)
|
|
|
|
|
|
|
|
! ---
|
|
|
|
|
|
|
|
int_fit = NAI_pol_mult_erf_ao_with1s(i, j, expo_fit, r, 1.d+9, r)
|
|
|
|
! if(dabs(coef_fit)*dabs(int_fit) .lt. 1d-12) cycle
|
|
|
|
|
|
|
|
tmp += coef_fit * int_fit
|
|
|
|
|
|
|
|
! ---
|
|
|
|
|
2024-01-15 12:02:38 +01:00
|
|
|
do i_1s = 2, List_env1s_square_size
|
2023-02-06 18:17:56 +01:00
|
|
|
|
2024-01-15 12:02:38 +01:00
|
|
|
coef = List_env1s_square_coef (i_1s)
|
2023-07-03 00:47:55 +02:00
|
|
|
if(dabs(coef) .lt. 1d-15) cycle ! beta = 0.0
|
2024-01-15 12:02:38 +01:00
|
|
|
beta = List_env1s_square_expo (i_1s)
|
|
|
|
B_center(1) = List_env1s_square_cent(1,i_1s)
|
|
|
|
B_center(2) = List_env1s_square_cent(2,i_1s)
|
|
|
|
B_center(3) = List_env1s_square_cent(3,i_1s)
|
2023-02-06 18:17:56 +01:00
|
|
|
dist = (B_center(1) - r(1)) * (B_center(1) - r(1)) &
|
|
|
|
+ (B_center(2) - r(2)) * (B_center(2) - r(2)) &
|
|
|
|
+ (B_center(3) - r(3)) * (B_center(3) - r(3))
|
|
|
|
|
|
|
|
alpha_1s = beta + expo_fit
|
|
|
|
alpha_1s_inv = 1.d0 / alpha_1s
|
|
|
|
centr_1s(1) = alpha_1s_inv * (beta * B_center(1) + expo_fit * r(1))
|
|
|
|
centr_1s(2) = alpha_1s_inv * (beta * B_center(2) + expo_fit * r(2))
|
|
|
|
centr_1s(3) = alpha_1s_inv * (beta * B_center(3) + expo_fit * r(3))
|
|
|
|
|
|
|
|
expo_coef_1s = beta * expo_fit * alpha_1s_inv * dist
|
|
|
|
if(expo_coef_1s .gt. 80.d0) cycle
|
|
|
|
coef_tmp = coef * coef_fit * dexp(-expo_coef_1s)
|
|
|
|
if(dabs(coef_tmp) .lt. 1d-12) cycle
|
|
|
|
|
|
|
|
int_fit = NAI_pol_mult_erf_ao_with1s(i, j, alpha_1s, centr_1s, 1.d+9, r)
|
|
|
|
|
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|
|
tmp += coef_tmp * int_fit
|
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|
|
enddo
|
|
|
|
|
|
|
|
! ---
|
|
|
|
|
|
|
|
enddo
|
|
|
|
|
2024-01-15 12:02:38 +01:00
|
|
|
int2_u_grad1u_env2(j,i,ipoint) = tmp
|
2023-02-06 18:17:56 +01:00
|
|
|
enddo
|
|
|
|
enddo
|
|
|
|
enddo
|
|
|
|
!$OMP END DO
|
|
|
|
!$OMP END PARALLEL
|
|
|
|
|
|
|
|
do ipoint = 1, n_points_final_grid
|
|
|
|
do i = 2, ao_num
|
|
|
|
do j = 1, i-1
|
2024-01-15 12:02:38 +01:00
|
|
|
int2_u_grad1u_env2(j,i,ipoint) = int2_u_grad1u_env2(i,j,ipoint)
|
2023-02-06 18:17:56 +01:00
|
|
|
enddo
|
|
|
|
enddo
|
|
|
|
enddo
|
|
|
|
|
|
|
|
call wall_time(wall1)
|
2024-01-15 12:02:38 +01:00
|
|
|
print*, ' wall time for int2_u_grad1u_env2 (min) = ', (wall1 - wall0) / 60.d0
|
2023-02-06 18:17:56 +01:00
|
|
|
|
|
|
|
END_PROVIDER
|
|
|
|
|
|
|
|
! ---
|
|
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|
|