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Tuned selection
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@ -46,11 +46,11 @@ subroutine update_pt2_and_variance_weights(pt2, variance, norm, N_st)
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i_iter = 1
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i_iter = 1
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endif
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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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do k=1,N_st
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! rPT2
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! rPT2
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rpt2(k) = pt2(k)* (1.d0 + 1.d0/(1.d0 + norm(k)))
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rpt2(k) = pt2(k)/(1.d0 + norm(k))
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enddo
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enddo
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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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avg = sum(pt2(1:N_st)) / dble(N_st) - 1.d-32 ! Avoid future division by zero
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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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variance_match_weight(k) *= product(memo_variance(k,:))
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enddo
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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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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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max(threshold_davidson, 1.e-1 * PT2_relative_error * minval(abs(pt2(1:N_states)))) )
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