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Merge branch 'dev' of github.com:QuantumPackage/qp2 into dev
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@ -29,7 +29,7 @@ subroutine update_pt2_and_variance_weights(pt2, variance, norm, N_st)
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double precision, intent(in) :: variance(N_st)
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double precision, intent(in) :: norm(N_st)
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double precision :: avg, pt2_rpt2(N_st), element, dt, x
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double precision :: avg, rpt2(N_st), element, dt, x
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integer :: k
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integer, save :: i_iter=0
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integer, parameter :: i_itermax = 1
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@ -46,16 +46,16 @@ subroutine update_pt2_and_variance_weights(pt2, variance, norm, N_st)
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i_iter = 1
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endif
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dt = 1.0d0
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dt = 2.0d0
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do k=1,N_st
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! PT2 + rPT2
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pt2_rpt2(k) = pt2(k)* (1.d0 + 1.d0/(1.d0 + norm(k)))
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! rPT2
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rpt2(k) = pt2(k)/(1.d0 + norm(k))
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enddo
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avg = sum(pt2_rpt2(1:N_st)) / dble(N_st) - 1.d-32 ! Avoid future division by zero
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avg = sum(pt2(1:N_st)) / dble(N_st) - 1.d-32 ! Avoid future division by zero
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do k=1,N_st
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element = exp(dt*(pt2_rpt2(k)/avg -1.d0))
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element = exp(dt*(pt2(k)/avg -1.d0))
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element = min(2.0d0 , element)
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element = max(0.5d0 , element)
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memo_pt2(k,i_iter) = element
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@ -71,6 +71,12 @@ subroutine update_pt2_and_variance_weights(pt2, variance, norm, N_st)
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variance_match_weight(k) *= product(memo_variance(k,:))
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enddo
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if (N_det < 100) then
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! For tiny wave functions, weights are 1.d0
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pt2_match_weight(:) = 1.d0
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variance_match_weight(:) = 1.d0
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endif
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threshold_davidson_pt2 = min(1.d-6, &
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max(threshold_davidson, 1.e-1 * PT2_relative_error * minval(abs(pt2(1:N_states)))) )
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@ -326,7 +332,7 @@ subroutine select_singles_and_doubles(i_generator,hole_mask,particle_mask,fock_d
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i = psi_bilinear_matrix_rows(l_a)
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if (nt + exc_degree(i) <= 4) then
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idx = psi_det_sorted_order(psi_bilinear_matrix_order(l_a))
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if (psi_average_norm_contrib_sorted(idx) > 0.d0) then
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if (psi_average_norm_contrib_sorted(idx) > 1.d-20) then
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indices(k) = idx
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k=k+1
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endif
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@ -350,7 +356,7 @@ subroutine select_singles_and_doubles(i_generator,hole_mask,particle_mask,fock_d
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idx = psi_det_sorted_order( &
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psi_bilinear_matrix_order( &
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psi_bilinear_matrix_transp_order(l_a)))
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if (psi_average_norm_contrib_sorted(idx) > 0.d0) then
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if (psi_average_norm_contrib_sorted(idx) > 1.d-20) then
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indices(k) = idx
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k=k+1
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endif
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